2013 in review

January 1, 2014

The WordPress.com stats helper monkeys prepared a 2013 annual report for this blog.

Here’s an excerpt:

The concert hall at the Sydney Opera House holds 2,700 people. This blog was viewed about 12,000 times in 2013. If it were a concert at Sydney Opera House, it would take about 4 sold-out performances for that many people to see it.

Click here to see the complete report.


Color Measurement Technology and Its Applications

June 10, 2013


I would like to share my thoughts on color technology and its application.
Technology has always been more than factories and machines.
Technology includes techniques, as well as machines that may or may not necessarily to apply them.
Color measurement technology land marks are:
1 ) 1931 Kubelka-Munk theory
2) 1931 CIE Standard Observer
3) 1931-1935 First GEC Recording Spectrophotometer
It took over 50 years for establishing the color measurement technology. After the introduction of computer, its progress is phenomenal. I remember CIE Golden Jubilee Seminar held in London in 1981. It was a great conference on color measurement and its applications.Today, very accurate and highly reliable color measuring spectrophotometers are available. Very fast computing is possible. What is needed is better theory for match prediction. The Kubelka – Munk theory only considers forward and reverse light fluxes. It is called two flux models. By considering fluxes in other directions, four -, six-, up to 26 fluxes have been developed. It is called Multi- Flux theory. It considers multiple scattering problems. The practical evaluation of these theoretical advances is still largely lacking. Multi flux models have not shown increased accuracy in match prediction, except in case of translucent plastics. It assumes no crowding of pigment particle occurs, i.e. at relative low pigment volume concentration it works. Using K – M theory, we may get inaccuracies in predictions but it can be corrected easily by subsequent correction program. We have to have better theory for match prediction.

Today, advances in computers, electronics, optics and techniques of coloration are changed and still changing very fast. You are aware of the fact that technology feeds on itself. Technology makes more technology possible. Technological innovation consists of three stages :
1) Creative feasible ideas- for example , measurement of color introduced in 1931
2) Practical application – for example , Colorant Mixture Computer (COMIC) introduced in 1962
3) Diffusion through Society: The activity to popularize the concept of color measurement and its application in paints, plastics, inks and textiles through professional Societies,training programs conducted by University departments and technical seminars organised by color system suppliers.
If the above process is complete, it generates again new creative ideas or concepts. Time – gap between two technological innovation decreases the time between the original concept and practical application and its use has been decreasing and we have to see that delays between idea and application are almost unthinkable and in present context we must remember that we talk of appropriate technology or low cost technology for the end user. Application and diffusion stage is to be considered for generating new concepts of technology.
No doubt that computer color matching technique made possible sophistication in color control offering better economies.
However, we must remember that any new technology is to be used in new ways:
– It is to be adapted,
– Refined,
– Altered,
– or otherwise changed.
This is to make it SUPER MACHINE ( Advanced Color Control System)
We have to use existing knowledge of color technology for controlling and changing the coloring processes.
Now, we look forward for new low cost, highly accurate, portable color sensors, new color match prediction theory, web based color software, cloud computing and mobile phone based technology for digital color communication.Let us see what new things are going to come and shape the new coloring world.

Dr Narendra S Gangakhedkar

Contact: drnsg@rediffmail.com


May 19, 2013

One of the most common problems to solve in the dye related industries is that of determining the strength of a dye relative to that of another one used as standard. Everyone is aware of the economic importance of this color related property of the dye. The strength is defined as dyer has to use ‘ X’ parts of test dye ‘B’ to obtain an identical coloration to that obtained with 100 parts of the standard dye ‘A’. If dyes are physically or chemically identical, then the strength of the test colorant will be weaker or stronger. This comparison is correct if you are buying dye from the same manufacturer. When two dyes are different, at least in part, chemically or physically or both (say different dyes of same hue or same dyes of different manufacturers), then the strength comparison becomes complicated. Not only the strength but chromatic changes (tonal variations) have also to be considered.

Dye applications and pigment applications are quite different and one has to analyze it differently. Color strength, or tinctorial value of a pigments is defined as its ability to impart color to other materials. The lower the concentration of a colored pigment required to achieve a defined impression of color that is a given depth of a shade, the greater is color strength of colored pigments. It depends on the absorption coefficient (K) of colorant. The higher the absorption coefficient, the higher will be the strength of colorants, on the other hand, reducing power of TiO2 white (Tinting Strength of white) depends on the scattering coefficient (S). More the scattering, better will be reducing power. Black scatters least and absorbs most, while white scatters most and absorbs least. Some of the pigments such as yellows, reds and oranges scatter a lot and one cannot neglect their scattering power. One has to use both the optical parameters (K and S).

The complicated problem of strength assessment is simplified by color strength calculation.
Testing is made against a specimen of the identical colorant which has been stated as being the standard or reference; it is to be tested as per the procedure recommended and close to coloring process. While evaluating the strength, the same procedure is to be followed for making samples of the standard and the batch simultaneously.

Strength of any colorant (dyestuff / pigment) is related to absorption property. We measure reflectance and not absorbance. It is known to us that when reflectance is more, absorbance is less and when reflectance is less, absorbance is more. Kubelka – Munk theory gives us the following relation between reflectance and absorbance:

K/S = [{(1-R) 2 / 2R}]

Where R is the reflectance, K is absorbance and S is the scattering. K/S  Vs Wavelength curve is always characteristics of every colorant.

Color Strength is defined as:

Color Strength = [(K/S) Batch / (K/S) Standard] x 100

One can determine color strength using following different methods:

1. R Min (Absorbance Maxima)

2. At given Wavelength

3. Based on Tristimulus Values.

– X

– Y

– Z

– X & Y (Average)

– Z & Y (Average)

4. Integrated Wavelengths.

There is too much confusion in selecting the method for strength calculation. One has to choose the method with great care.

R Min

One can find the lowest value of R (which is maximum value of absorbance) and obtain K/S values of sample and the standard and compute the strength. This is generally accepted and more or less agrees with visual observation. In most of the available color software packages, it is automatically done by the program. Fig.1 illustrates the strength computed at RMin.

stregth wvelength

Figure 1: Color Strength at R min

Given Wavelength

This option is selected when you are comparing two dyes or pigments, which may be having different R minima. In such cases, you have to compute the strength based on R Min wavelength of the standard. This will give you the correct picture of the strength. If  the Standard is manufactured by one company and  the incoming dye lot is manufactured by different company then R Min will be different for the two. In such case, we have to use  the R Min wavelength of the Standard for the computation of strength. That is called the strength at given wavelength. It is illustrated in Fig.2.

strength 580

Figure 2: Color Strength at Given Wavelength

Tristimulus Value

This option is used when you are having measurement with colorimeter having three filters.  If colorants are Red / Green, then use the ratio of X – Tristimulus value and if colorants are Yellow / Blue, then use ratio of Z – Tristimulus values. If you want to consider the light / dark property of colorants then  use the ratio of Y Tristimulus values. It is ideal to use combinations such as average of X and Y (for Red / Green) and Z and Y (for Yellow/ Blue). This will take into consideration the effect of lightness/darkness. In case of Black and White colorants , one can use the ratio of Y -tristimulus value. This method is not much useful in dye application. But in case of pigment application, it is found very useful for high chroma yellow, red and orange pigments. Figure 3 is the output for the strength based on X value, Figure 4 is based on Y value and Figure 5 is based on Z value.

strength x

Figure 3: Color Strength calculated using X – Tristimulus Value

strength y

Figure 4:Color Strength calculated using Y -Tristimulus Value

strength z

Figure 5: Color Strength calculated based on Z- Tristimulus Value

Integrated Wavelength

Some of the laboratories and available color software packages are using integrated wavelength approach for computation of strength. In this case strength is calculated at each wavelength and average is taken as real strength of the colorant. This is becoming more and more popular. Sometimes, it may not give correct strength idea of the colorant as reflectance values are changing wavelength to wavelength. Strength at R Min is the correct representative but strength based on integrated wavelength is preferred by most of the users. In case of mixture dyes, it is found very useful. This is useful if the dye is a mixture dye such as brown, black , orange and olive.

The results of various calculations will differ. The choice of mode of calculations depends on the user’s experience in specific cases. The true answer could be based on perception of equality of depth. One has to obtain extensive visual determinations of the perception of equality of depth. This is a major problem in visual assessment of depth. One must be very careful while interpreting the data.

One can also look at the color difference and hue change (h- Hue angle). Using CIE Diagram (x, y), one can find out the purity and dominant wavelength. If there is no change in dominant wavelength, then there will be no hue change in dyes which are compared.

It is my opinion that in case of textile application, Saunderson correction is not required but we have  to use the same in pigment applications.

Strength and Color Difference Relationship

One has to look at the strength and color difference “AS IT IS” and “AFTER ADJUSTMENT” of strength. This is based on mathematical calculation .After adjustment of strength, it may be acceptable but color difference will be too much or strength may not be acceptable but color difference will be within tolerance limit. This is  illustrated in Figure 6.

strength as is after

Figure 6: Color Difference ” As it is ” and ” After Adjustment”

Many times, you may get higher strength of colorants. Generally, when the strength of the dye is high, you can adjust it by loading less. Taking this practical approach into consideration, mathematically you can predict the reflectance / absorbance curve of any given sample and predict the expected color difference after adjustment of the strength. Most of the color software  packages give data on  strength and color difference” AS IT IS” and  strength and color difference data  “ After the Adjustment”.

Fig. 6  Illustrates the computer output for the strength. One can see that strength of the dye is 110.69 with a color difference of 1.97. After adjusting the 10.69% of the strength, color difference will reduce to 0.95 units from 1.97. This may be acceptable. Sometimes, you may find increase in color difference value after adjustment of the strength.That will creat more problems for the dyer. One should remember that one has to take into consideration both the parameters, strength and color difference. One must fix a tolerance limit for the strength and also note that color difference of the batch after adjustment of the strength should be within required tolerance limit.

Figure 7  Illustrates the dye strength calculations using different methods mentioned above. Jade Green Standard and batch samples of 1% concentration were measured and dye strength was calculated using  different methods. In this particular case variation was not significant but it is noticed that strength value is different for different methods. The author’s experience is that the strength at Rmin is always a correct representative.

Dye str with diff methods

Figure 7: Dye Strength Calculation using Different Methods

Dye Application (Textiles)

In case of textile application, substrate material scatters and dye absorbs. When we want to compare strength of a dye, we have to dye standard and batch using the same substrate with same concentration and exactly the same dyeing method. As substrate is constant, we can easily compare the color strength as mentioned above.

Many times, dyers make an assumption that if the in-coming batch of the dye is having higher strength (say, 5 to 10 % more ), they will be able to reduce the cost of dyeing. The fact is that they will not get the matching in first shot and adjustment will be difficult. Let us say, you have three dyes in a combination (Red, Green and Blue). Batch Red is greener and 10 % strong, batch blue is redder and 5% weak and Green is yellowish and 3 % strong. In such situation, you will adjust the formula using the strength computation but color difference cannot be adjusted and you have to reformulate the recipe. One has to control the strength and color difference. The problem of lightness/ darkness is noticed in some cases. As the sample is darker, one feels that it is deeper in strength. Dirty tone does not mean that it is deeper or stronger.This creates confusion.

There are problems when you are comparing similar dyes manufactured by different manufactures. Colorants are produced from chemical intermediates and by different production processes. The purity of the products used, the process of synthesis and subsequent finishing determine the properties of products. Global salts used in the process play very important role in final strength of the dye produced. It is well known that different dye lots of varying properties are blended and global salts  or diluents are used for adjusting higher tinctorial values .Mixture dyestuff are also made from waste by dye manufacturer. All these affect the final color quality and mainly strength is affected to a large extent.

If the same dye is manufactured by different manufacturers, one should look at R min of these two lots and if it is not the same, then use the R min of the standard for computation of strength. Generally, if R min is different, it is hue difference between the two lots.  This can be confirmed by finding out the dominant wavelength from CIE diagram. If it is significantly different say, about 2-3 nm wavelength difference, then it is to be considered as a new dye. It may be due to different chemical constituents used in the process.

The dyestuff manufacturers can always adjust the strength of batches as they are mixing lots of different production batches having different strength. They also use global salts or diluents for reducing the strength if it is on higher side. One should fix a tight tolerance limits for strength and chromaticity. For textile processor, there is no alternative left but to reject the lot or reformulate all those shades which are to be matched with batch lots.  Every textile dye house should demand a quality assurance certificate from the colorant manufacturer. If this is done, major problems of dyers are solved. During my industrial experience, I have found a few  colorant manufacturers who used to give quality assurance certificate for each dye lot produced and supplied. It was assured that strength is +/- 2 % and tonal variation (color difference) is within accepted tolerance limits. Supplier used to send color data by fax or e-mail. It is quite in advance before the colorant lot is received by the factory. This has solved many problems at both ends. Very stringent control of incoming colorant lots leaves the colorant manufacturer no other choice but to supply colorants with acceptable tolerance limits.Colorant manufacturers will certainly extend their cooperation as they are dependent on buyer. You must request for spectrophotometric curves of each dye supply. This will also reduce the load on lab analysis.

One can look at the variation noticed in in-coming batches of dye lots. Figure 8,  illustrates the statistical data of 70 batches of the dye received by the Dye House. The Figure 9, clearly indicates variation in strength and color difference. This statistical data is reported by P Ravichandran and I am using this information for explanation.

stat 70 dyes

Figure 8: Statistical data on Strength of Dye Lots

stat st and de 70 dyes

Figure 9: Statistical data on Strength of Dye Lots

Pigment Application (Paints, Plastics and Inks)

Tinting strength of  Universal colorants or machine colorants  affects the paint match and one has to control the same by having pass/fail tolerance limits for strength and chromaticity.

In tinted based formulation, reducing power of white bases is equally important as tinting strength of colorants.We have to control the tinting strength of colorants (universal colorants or machine colorants) and reducing power of white bases. If white base is not controlled or any of the colorant’s strength is not controlled, one will face problem. Main reasons are:

1. Non- standardized. Pigments – Chromatic and strength differences of incoming colorant lots.
2. Non- standardized dispersions- Even if incoming colorants are of good quality, because of improper dispersions in the process, the strength of tinting pastes are not within tolerance limit resulting into color correction.
3. Non-standardized tinting pastes – One has to control the color strength of each tinting paste produced.
4. Universal colorants or Machine colorants – One has to have strict control on universal colorants or machine colorants used. Variation in colorant strength should not be more than +/- 1 percent. It should not have any significant chromatic difference.

We have to make proper samples for color strength evaluation. For pigments, we have to mix color pigment with white TiO2. For inorganic pigments, we should use 25 parts of color pigment and 75 parts of white TiO2. For organic pigments, we should use 5 parts of pigment and 95 parts of white. In case of black, we should use 1 or 3 parts of black and 99 or 97 parts of white. Both standard and in-coming batch of colorants are to be mixed with the same white pigment and proper dispersion is to be achieved keeping all process parameters same. Tinting pastes and universal colorants or machine colorants are to be tested in the same way. Color strength is already defined earlier .But in case of white pigment; we call the Tinting Strength of white  as Reducing Power of white which depends on the scattering power of white and not on the absorbance property.

QCHECK for White TiO2

In case of white, one can find the reducing power of white by inverting the formula of color strength which is as follows:

Reducing Power = [(K/S) std / (K/S) bat] x 100

One can also determine the strength by adjusting Y value. In case of white, while preparing sample, one must use reduction with Green or Black pigment. It is found that one can make better visual assessment of white by reducing with green pigment. One can use 5 parts of organic green pigment with 95 parts of white. If you want to compare different white Tio2 pigments, it is better to compute absolute Scattering coefficients (S) using K-M equation. Higher the S value, better will be reducing power of white. Hiding Power being directly proportional to S value, you will achieve better hiding power of white base paint.

For making visual assessment of pigment,many times  masstone is prepared. But it does not give correct idea of strength  because of very low reflectance values. We get erratic results if R value is not correct because of flattening of the curve.It is better to make reduction with white.
There is no need to make Saunderson correction while computing colorant strength as we make standard and batch samples with the same resin or medium. The gloss level will be the same in the standard and the batch.

Remember, you must “Look and Think”. Look into sample visually and interpret the data of color strength and chromaticity carefully, otherwise you will be in trouble. In order to avoid corrections in production, one must control the strength and chromaticity of colorants.

The history of “color revolution” : Mauveine and Indigo

May 10, 2013

The total number of dyes discovered is more than three Millions and some 27,000 had been marketed and about two new ones are  appearing each week. Now, it is 2013. Numbers are certainly much more. Around 34,500 dyes and pigments are listed under 11,570 Color Index Generic Names  in fourth edition of Color Index International of SDC & AATCC.

In 1834, Runge, a German Chemist,noticed that upon distilling coal tar, aniline would give a bright blue color if treated with bleaching powder. That helped to pave the way to the development of aniline dyes. After 22 years, German Professor, August Wilhem Hofmann at London’s Royal College of Chemistry (now part of Imperial College, London) was interested in coal tar derivatives. The initial breakthrough happened by chance. In 1856, one of the Hofmann’s students Wlliam Henry Perkin was attempting to synthesize quinine.

Hofmann had published a hypothesis on how it might be possible to synthesize quinine, an expensive natural substance much in demand for the treatment of malaria. Perkin, who had by then become one of Hofmann’s assistants, embarked on a series of experiments to try to achieve this end. During the Easter vacation in 1856, while Hofmann was visiting his native Germany, Perkin performed some further experiments in the crude laboratory in his apartment on the top floor of his home in Cable Street in east London.

perkin mauve

Wlliam Henry Perkin

Since these experiments were not part of the work on quinine which had been assigned to Perkin, he and his partners carried them out in a hut in Perkin’s garden, so as to keep them secret from Hofmann. He obtained only a disheartened black sludge. Instead of throwing it away, he tried diluting it with alcohol and found that solution was purple. He discovered that it would dye silk and that it was possessed of a quality which is of paramount importance to the dyeing industry. It was resistant both to washing and to fading effects of light.

They satisfied themselves that they might be able to scale up production of the purple substance and commercialize it as a dye, which they called mauveine. Their initial experiments indicated that it dyed silk in a way which was stable when washed or exposed to light. They sent some samples to a dye works in Perth, Scotland, and received a very promising reply from the general manager of the company.

Having invented the dye, Perkin was still faced with the problems of raising the capital for producing it, manufacturing it cheaply, adapting it for use in dyeing cotton, gaining acceptance for it among commercial dyers, and creating public demand for it. However, he was active in all of these areas: he persuaded his father to put up the capital, and his brothers to partner him in the creation of a factory; he invented a mordant for cotton; he gave technical advice to the dyeing industry; and he publicized his invention of the dye.

Perkin borrowed his father’s life savings and put the dye into commercial production. It was named as MAUVE derived from the delicate purple of mallow flower.

Public demand was increased when a similar color was adopted by Queen Victoria in England and by Empress Eugénie, wife of Napoleon III, in France, and when the crinoline or hooped-skirt, whose manufacture used a large quantity of cloth, became fashionable. Fashionable Queen Victoria wore a mauve dress to the great exhibition of 1862; a penny stamp was printed in mauve .Everything seemed to fall into place by dint of hard work, with a little luck, too. Perkin and he became rich. After the discovery of Mauveine, many new aniline dyes appeared (some discovered by Perkin himself), and factories producing them were constructed across Europe. A new industry begun.

queen mauve dress

Queen Victoria

The plant dye industries began to be threatened when it was realized that the supply of new synthetics was easier to control. This was the case with Indigo. Von Bayer synthesized synthetic Indigo in 1878 and it was not marketed until 1897.

Indigo dye is an organic compound with a distinctive blue color. Historically, indigo was a natural dye extracted from plants, and this process was important economically because blue dyes were once rare. Nearly all indigo dye produced today — several thousand tons each year — is synthetic. It is the blue of blue jeans.
The demand for indigo in the 19th century is indicated by the fact that in 1897, 7000 square kilometers were dedicated to the cultivation of indican-producing plants; mainly in India India is believed to be the oldest center of indigo dyeing in the Old World. It was a primary supplier of indigo dye, derived from the plant Indigofera tinctoria, to Europe as early as the Greco-Roman era.
Indigo is one of the colors on Newton’s color wheel. Isaac Newton introduced indigo as one of the seven colors in his spectrum. In the mid-1660s, when Newton bought a pair of prisms at a fair near Cambridge, the East India Company had begun importing indigo dye into England, supplanting the homegrown woad as the source of blue dye. Indigo is a deep and bright shade of blue Color is named after the blue dye derived from the plant Indigofera tinctoria and related species. The color is placed on the electromagnetic spectrum between about 420 and 450 nm in wavelength, placing it between blue and violet

Production of Indigo dye in a BASF plant (1890)

Indigo was the first to synthesize. A discovery so valuable that BASF the German company invested 17 years and over 1,000,000 pounds in developing an economic method of producing the world’s first fast blue.

In 1897, 19,000 tons of indigo were produced from plant sources. Largely due to advances in organic chemistry, production by natural sources dropped to 1,000 tons by 1914 and continued to contract. These advances can be traced to 1865 when the German chemist Adolf von Baeyer began working on the synthesis of indigo. He described his first synthesis of indigo in 1878 (from isatin) and a second synthesis in 1880 (from 2-nitrobenzaldehyde). The synthesis of indigo remained impractical, so the search for alternative starting materials at BASF and Hoechst continued. The synthesis of N-(2-carboxyphenyl) glycine from the easy to obtain aniline provided a new and economically attractive route. BASF developed a commercially feasible manufacturing process that was in use by 1897. In 2002, 17,000 tons of synthetic indigo were produced worldwide.

Its success proved the Coup de graceto Indigo farming in India, where production dropped from 19000 tons in 1856 to 1100 tons in 1914 devasting the livelihood of Indian peasantry.

Indigo, India and Indigo Revolt

Indigo was used in India, which was also the earliest major center for its production and processing. The Indigofera tinctoria variety of Indigo was domesticated in India. Indigo, used as a dye, made its way to the Greeks and the Romans, where it was valued as a luxury product.
Indigo is among the oldest dyes to be used for textile dyeing and printing. Many Asian countries, such as India, China, and Japan and South East Asian nations have used indigo as a dye (particularly silk dye) for centuries. The dye was also known to ancient civilizations in Mesopotamia, Egypt, Greece, Rome, Britain, Mesoamerica, Peru, Iran, and Africa.
India is believed to be the oldest center of indigo dyeing in the Old World. It was a primary supplier of indigo to Europe as early as the Greco-Roman era. The association of India with indigo is reflected in the Greek word for the dye, indikón (ινδικόν, Indian). The Romans latinized the term to indicum, which passed into Italian dialect and eventually into English as the word indigo.
The Indigo revolt was a peasant movement and subsequent uprising of indigo farmers against the indigo planters that arose in Bengal in 1859. The back stage of the revolt goes back half a century when the indigo plantation act was established. After the courageous fight by the Sepoy for independence in 1857 in February–March 1859 the farmers refused to sow a single seedling of indigo plant. The strength of the farmers’ resolutions was dramatically stronger than anticipated from a community victimized by brutal treatment for about half a century. Most importantly it was a revolt of both the major religious groups of farmers in Bengal, notably a farmer Haji Molla of Nischindipur said that he would “rather beg than sow indigo”. The farmers were in no possession of any types of arms, it was totally a nonviolent resistance. The revolt started against the planters. It spread like wildfire in Bengal. Indigo planters were put into public trial and executed. The indigo depots were burned down. Many planters fled to avoid being caught. The zamindars were also targets of the revolting peasants. The revolt was ruthlessly suppressed. Large forces of police and military backed by the British Government and the zamindars mercilessly slaughtered a number of peasants. In spite of this the revolt was fairly popular, involving almost the whole of Bengal. The revolt had a strong effect on the government, which immediately appointed  the “Indigo Commission” in 1860. In the commission report, E. W. L. Tower noted that “not a chest of Indigo reached England without being stained with human blood”.

indigo factory in Bengal

Indigo Factory in Bengal

Denim Era
Denim is a tone of Indigo Crayola . It resembles the shade of indigo used in denim. Crayola created this color in 1993 as one of the new 16 colors.
In the 1960s, denim symbolized youth culture because so many young baby boomers wore denim jeans.

The development of new vat dyes went some way to solving the fastness crises.

In late fifteens, dramatic range of dyestuffs was discovered by ICI (Procion dyes -brightly colored dyes). These were the  first range of reactive dyes produced in 1956. This made a major impact on industry as well as textile dyers ( called textile artists) around the world. Procion reactive dyes have now become the “bread and butter” of dyeing trade.

The color revolution is started with synthetic chemistry of dyes (Mauve and Indigo) and has made tremendous impact on coloring process. This is the interesting part of the history of color revolution.

Color physics concept was first introduced by Newton and we started quantifying color. Color Chemistry revolution mentioned above has changed the coloring processes and  now ,we are able to predict color formula for any given color using modern technique of computer color matching .


William Henry Perkin







Color Index International:  http://www.colour-index.org

Cause and effect of color

April 26, 2013

Scientists analyze color and Artists manipulate color. Goethe was the artist and Newton was the  Scientist. Goethe offered his “Theory of Color “after disagreeing with what Newton has said about the color. To me, Newton was more concerned with the cause of color while Goethe was concerned with the effect of color. It is interesting to know the differences between these two thinkers.


Isaac Newton

Early in 1790, some 63 years after the death of Sir Isaac Newton, Johann Wolfgang Von Goethe looked at the white wall through prism he had borrowed. He expected to see the whole wall break out in colors of spectrum, but was amazed to find that the wall remained as white as before. He immediately spoke out loud to himself, though instinct, that Newtonian theory was erroneous. There was then no longer any thought of returning the prisms.

Although this condemnation of Newton was over-hasty, to say the least. It provided Goethe with the impetus for 20 years experimentation with color, culminating in publication of his massive Farbenlehre or Color Theory, in 1810. And extra ordinary Goethe, the poet, novelist, natural philosopher and creator of immortal Faust-saw it as his greatest work.

Theory of Colours (original German title Zur Farbenlehre) is a work by Johann Wolfgang von Goethe about the poet’s views on the nature of colours and how these are perceived by humans. Published in 1810, it contains some of the earliest published descriptions of phenomena such as coloured shadows, refraction, and chromatic aberration.

Goethe observed that color arises at the edges, and the spectrum occurs where these colored edges overlap.


Johann Wolfgang Von Goethe

His aim was to rescue color from the atomic restriction and isolation in which it has been banished, in order to restore it to dynamic flow of life and action. In other words, the abstract mathematics of optics completely fails to do justice to experience of color in everyday life.

To Goethe, the Newtonian approach to color was rather like describing a rosé in terms of a collection of uniformly grey subatomic particles, it completely ignored the essence and beauty of flower.

Although Goethe’s work was rejected by physicists, a number of philosophers and physicists have concerned themselves with it, Goethe’s book provides a catalogue of how color is perceived in a wide variety of circumstances, and considers Isaac Newton’s observations to be special cases. Unlike Newton, Goethe’s concern was not so much with the analytic treatment of colour, as with the qualities of how phenomena are perceived. Philosophers have come to understand the distinction between the optical spectrum, as observed by Newton, and the phenomenon of human colour perception as presented by Goethe.

He was more concerned with physiological aspect of color and not physical aspect of color. His main concern was perception of color.

He wanted instead to classify the different conditions under which color is produced and to assess their reality in terms of ordinary experience.

Subjective Experiments – Objects are looked at through mediums (Goethe’s approach)

Objective Experiments – Light pass through medium that is looked at – physical and medium-glass prism. (Newton’s approach)

At Goethe’s time, it was generally acknowledged that, as Isaac Newton had shown in his Opticks in 1704, colourless (white) light is split up into its component colours when directed through a prism.

“Along with the rest of the world I was convinced that all the colours are contained in the light; no one had ever told me anything different, and I had never found the least cause to doubt it, because I had no further interest in the subject. But how I was astonished, as I looked at a white wall through the prism, that it stayed white! That only where it came upon some darkened area, it showed some colour, then at last, around the window sill all the colours shone… It didn’t take long before I knew here was something significant about colour to be brought forth, and I spoke as through an instinct out loud, that the Newtonian teachings were false  –  Goethe  

Newton never claimed that he was accounting for the whole phenomenon of color. He was simply more interested in light – the cause of color – not the effect of color.Based on his experiments with turbid media, Goethe characterized color as arising from the dynamic interplay of darkness and light. Goethe pictures to himself that light and darkness relate to each other like the north and South Pole of a magnet. The darkness can weaken the light in its working power. Conversely, the light can limit the energy of the darkness. In both cases colour arises.

Goethe writes:
“Yellow is a light which has been dampened by darkness; Blue is darkness weakened by light”.
Goethe thought that light should not be broken down – it should be treated as whole – The colors produced by the light are to be studied in natural habitat – The outside world was Goethe’s laboratory.

“Seeing” – he insisted, depends on perception of light reflected from an object in relation to light that falls on it. If we are uncertain about the light source, we cannot be certain about color, or even in nature of the object.

If yellow dress is seen in day light – it is yellow, but if yellow light is substituted for daylight it is impossible to say whether the color is due to dress or light. In any case a white dress would look exactly the same. Therefore it is essential to know the way in which object darkens the light and to what extent.

Goethe anticipated Ewald Hering’s Opponent process theory by proposing a symmetric color wheel. Theory of opponent color now explains the color phenomenon to some extent. Physiology and psychology of color is now equally important for understanding the complete concept of color.

Now, we have better understanding of color based on modern color science which has taking into consideration physics,chemistry, physiology and psychology of color.

As a catalogue of observations, Goethe’s experiments are useful for understanding the complexities of human colour perception. Whereas Newton sought to develop a mathematical model for the behavior of light, Goethe focused on exploring how colour is perceived in a wide array of conditions. Developments in understanding how the brain interprets colors, such as color constancy and Edwin H. Land’s retinex theory bear striking similarities to Goethe’s theory.

Goethe was not concerned with the ultimate cause of color but only with its effect on the eye and the mind of the observer. He shifted attention from the light to the opacity of the atmosphere; the distant light, he said is darkened to yellow and reds by intervening atmosphere. So for the Goethe, yellow is the first color to appear when white is darkened and the blue the first when the black is lightened. These two colors yellow and blue – are two poles of a whole system of color pairs, each of which has opposing qualities plus/ minus, warm/ cool, active / passive. For him basic color pairs are yellow- blue, red- green and orange/ violet. Orange is formed by further darkening yellow and violet similarly from blue.

Due to their different approaches to a common subject, many misunderstandings have arisen between Newton’s mathematical understanding of optics, and Goethe’s experiential approach.Because Newton understands white light to be composed of individual colours, and Goethe sees colour arising from the interaction of light and dark, they come to different conclusions on the question: is the optical spectrum a primary or a compound phenomenon?

For Newton, the prism is immaterial to the existence of colour, as all the colours already exist in white light, and the prism merely fans them out according to their refrangibility. Goethe sought to show that, as a turbid medium, the prism was an integral factor in the arising of colour.
Whereas Newton narrowed the beam of light in order to isolate the phenomenon, Goethe observed that with a wider aperture, there was no spectrum. He saw only reddish-yellow edges and blue-cyan edges with white between them, and the spectrum arose only where these edges came close enough to overlap. For him, the spectrum could be explained by the simpler phenomena of colour arising from the interaction of light and dark edges.
Newton explains the appearance of white with coloured edges by saying that due to the differing overall amount of refraction, the rays mix together to create a full white towards the center, whereas the edges do not benefit from this full mixture and appear with greater red or blue components.

Goethe’s reification of darkness is rejected by modern physics. Both Newton and Huygens defined darkness as an absence of light. Young and Fresnel combined Newton’s particle theory with Huygens’s wave theory to show that colour is the visible manifestation of light’s wavelength. Physicists today attribute both a corpuscular and undulatory character to light — comprising the Wave–particle duality.

Goethe’s colour theory has in many ways borne fruit in art, physiology and aesthetics. But victory, and hence influence on the research of the following century, has been Newton’s.
— Werner Heisenberg, 1952

Goethe started out by accepting Newton’s physical theory. He soon abandoned it… finding modification to be more in keeping with his own insights. One beneficial consequence of this was that he developed an awareness of the importance of the physiological aspect of colour perception, and was therefore able to demonstrate that Newton’s theory of light and colours is too simplistic; that there is more to colour than variable refrangibility.
—Michael Duck, 1988


Goethe, Theory of Colours, trans. Charles Lock Eastlake, Cambridge, MA: MIT Press, 1982. ISBN 0-262-57021-1

Johann Wolfgang von Goethe , From Wikipedia, the Free Encyclopedia

Duck, Michael (September 1988). “Newton  and Goethe on Colour: Physical and physiological considerations”. Annals of Science, Volume 45, Number 5, pp. 507-519. Retrieved 2011-03-29.

Judd, Deane B. (1970). Introduction by Deane B. Judd, Goethe’s Theory of Colours. Cambridge: MIT Press. Retrieved 2007-09-14.


March 26, 2013


(Meaningful correlation with visual perception)

Colors do not match.

Product colors look different side-by-side.

Raw materials used for making colors are wasted.

Off – Colors do not sell.

Orders and shipments of any products are delayed due to miss match of color.

Product costs rise due to color recycle.

Right color just-in-time.

But colors can go wrong in a lot of ways.

Color on Demand and Color on Delivery.

Color Consistency, Part to Part, Item to Item – Order To Order, Plant to Plant – Supplier to Supplier.

Single Number Shade Passing: say, DE = 0.6 CIELAB Unit or DE = 0.7 CMC (2:1) Unit Accepted. Not really works.

Above mentioned sentences are always heard when we talk of delivering the right color at the right time.

Industries such as textiles, paints plastics, inks packaging, dyestuff and pigment have to deliver not only the right color but the color just in time. Color is the first impression of any product and one has to produce the same right first time with no deviation from the standard given. “COLOR ON DEMAND” is another pressure developed by marketing and the colorist has to struggle a lot for getting the desired color.

Modern colorists use established technology of Computer Color Matching (CCM). However, the advances in color technology are offering many new approaches for automation in coloration process.

Spectrophotometer, a color measuring instrument, can make the same kinds of judgment that human observers do. Our main objective in the use of color-measuring instrument is to find a meaningful correlation with visual perception. Please note that instrument is no- where near the versatility of the eye. Do you know why? Instrument recognizes only a specific attribute of an object, whereas the observer (we human beings) perceives a number of different attributes simultaneously. To simulate the complex visual process, one would need several different instruments, each designed to sense a specific attribute of the object. In comparing these instruments with eye, the following things are to be noted:

1. The eye is more versatile because of its sensitivity to geometric factors of direction, pattern, shape, and so on. However, its evaluations are subjective, disputable, variable with changes in viewing conditions and variable from observer to observer.

2. Instrument is less flexible than the eye, but it quickly reduces appearance to numbers that usually correlates well with visual evaluations. They provide evaluations that are more repeatable than those of the unaided eye.

3. Color and Gloss : We have to separate these two components. Appearance is a combination of color and gloss. Visually,we see total appearance and we do not know the contribution of gloss.Instrumentally ,we can separate these two components by measuring in two modes , specular component included ( gloss included) and specular component excluded mode.But it is difficult to make judgment with textured  samples in textile material because of orientation effect of different weaves. Now, same problem arises in textured paints or metallic paints.


Note that the eye can discriminate between small changes in x, y (chromaticity co-ordinates) in the violet region, while the eye is least sensitive to chromaticity changes in the green region of chromaticity diagram (Refer – Standard chromaticity chart).

Why Color difference measured by Tristimulus psychophysical methods may fail to correlate reliability with visual estimates of color difference?

1. It is now well known  that distance in uniform. tristimulus color space is not a proper measurement of the magnitude of observer response. It is not reasonable to expect that there is any sensor or device in the human brain taking the square root of the sums of the squares of three differences, as is done for distance in rectangular space

(DE) = [(DL) 2 + (Da) 2+ (Db)2]1/2

Rather the magnitude of color difference is more properly related to the component of the particular difference that is greatest. Other things being equal, it is reasonable to expect that the single component  which shows the greatest incremental difference will be the one which will be signaling most strongly for attention and recognition by the observer.

2 Numerical tristimulus values (X, Y, and Z) even though they are proper integrations of receptor spectral responses, may nevertheless fail to be valid measurements of neural signals.

3 When one is dealing with saturated colors sensitivity to small differences in hue always appears to be so much greater than sensitivity to small differences in saturation.

4. The hue difference corresponds to a change of balance in the opponent channels, whereas the saturation difference is involved mainly with one channel only. L a b type scales are based on opponent color theory of color vision which presumes that in the human eye there is an intermediate signal switching stage between the light receptors in the retina and the optic nerve taking color signals to the brain. In this switching stage, red responses are compared with green to generate a Red-to-Green color dimension. The yellow response is compared in similar manner with blue to generate yellow-to blue color dimension.


We use the tristimulus system (X, Y, and Z) to represent visual color difference evaluations. There are some reasons for lack of good correlation between visual and instrumental measurements. There are certain variables that may also contribute to poor correlation.

I) Variables in relation of color scales (L*, a*, b*) to actual perceived color differences. Because the CIE color scales do not provide either uniform or logical estimates of perceived color intervals or color relationship, other color scales such L*, a*, b*, FMC II ,L* C* h etc. were developed for making the color space more uniform.

1. Uniform color scales differ markedly from each other in dimensions.

2. The mode of observation (aperture, illuminant or object). In the object mode, the character of the object (metallic, transparent, liquid or turbid) introduces variability’s in judgment.

3. The magnitude of differences seen may not be the same when comparing readily discernible differences as that seen when the measurement involves just-perceptible threshold differences.

II) Variables in observing situation affecting visual estimates of color difference:

1. Level of illumination

2. Color of illumination

3. Diffusion and geometric uniformity of illumination

4. Proximity of specimen to each other

5. Size and flatness of specimens

6. Presence of gloss on specimens: Dark glossy specimens are said to have visually smaller color differences than dark matt specimens with the same reflectance factor, since the high gloss tended to mask small color differences.

7. Presence of Textures.

8. Surroundings and backgrounds for the specimens. Backgrounds on the gray side of the color of the specimens being compared are best for visual sensitivity to small differences.

III) Variables in the observer that affect his estimates of the magnitude of color difference:

1. Prior experience of observer and the difficulty he foresees in correcting the specimen to match the standard target color.

2. Prior adaptation to observing situation.

3. Color difference perceptibility and commercial acceptability do not always correlate.

a. Hue differences are less accepted than lightness and Chroma differences.

b. Mismatches on the yellow side of standard are more often rejected.

c. Acceptance practice varies with industry, with company, within industry and with economic practices.

4. There is variation among observers even about a judgment of “Perceptibility”.


Color difference tolerances are designed as boundaries in color space within which acceptable colors of the product fall. The boundaries do not necessarily correlate with perceptibility of difference but rather with the limits of acceptability. The standard color may not be in the center of the bounded region but may be displaced to one side. For example, where subsequent yellowing may occur, the tolerance of the yellow-blue dimension might be +0.1, -0.8 units. For defining such color difference tolerances, a three dimensional description of the color difference allowed can be considerably more helpful than a one-number tolerance such as DE (Total Color difference). A color difference expressed in terms of DL, Da, and Db. provides a better guide to the needed formulation correction. Such three term tolerances are readily reducible to graphs for showing acceptability.

No doubt, CIE L*C* h space is more uniform as compared to CIE L* a* b* space, yet it is better to have three dimensional pass/fail instead of single number (DE) pass/Fail.

A very small change in a tristimulus value, particularly in the red – green dimension, as indicated by the X-value, can represent a fairly substantial color difference. For many colors of practical interest a 0.02 variation (in X) causes a 1.0 DE Unit change, a fact which should concern the tolerance setter.


R S Hunter, “The Measurement of Appearance “.  A Wiley Inter Science Publication, John Wiley and Sons (1975)

Color correction strategy

March 12, 2013

In color match system,” Match” program offers you the best possible color formulations based on least cost and least metamerism.  One has to develop excellent database based on substrate – class of colorants – process combination ( Fig.1). .One has to make these variables ( substrate-dye- process ) as constants. One can achieve better results if these variables are controlled properly or understood perfectly. One can see the predicted formula along with quality of reflectance match. One can see from the output ( Fig.1) that predicted matches are categorized  (coded) based on three signal dots ( Red ,Orange and Green) . Green dot indicates that dye- selection combination will not give any problem in matching. Orange code indicates that combination may have one or two incompatible dyes and red code indicates that formula predicted is having incompatible dyes and this formula may give problem in reproducing the shade time to time. These color traffic signals give warning to colorist in advance.One has to incorporate such type of strategy in formulation and correction program.


Figure 1: Prediction of a Recipe based on Substrate-Class of Colorant-Process

The purpose of any color system is to match any given color” Right First Time (RFT)”. This will certainly achieve the reduction in time of coloring proces. With good matching program, one can achieve good matching in Laboratory and will be successful in transferring the Lab formula to Production. One may face a problem when one transfers the established recipe to production. One will not be in a position to catch the color in first shot. Right First Time (RFT) is your dream as colorist and anyone would like to get the desired color in “zero shot”. That means you do not want to do any tinting further. It is a little difficult situation even though you have standardized colorants, you have  assembled the batch accurately and you have controlled the coloring process minutely and accurately. In such situation, you have to correct the batch by using effective correction program. Sometimes, even in the Laboratory, you have to repeat the process of coloration for getting a perfect match.  You have to have good correction program which considers all  the parameters which affect the  final color in production.

There are number of color software packages available in the market. Most of them offer good” Match” programs. You have to evaluate these color software packages for correction program module even though match and QC modules are working excellent. In any good color software package, color correction strategy used is the most important factor and decides the quality of color software. Logic used in correction program is shown below:

correction logic

Logic Used in Correction Program : Iteration Method

I have worked on number of color software packages available in the market. During last few years, almost every color software company has offered new software versions after every three or four years. Each new version was refined and it was much better and something new or novel. However, it is very difficult to make comparison with each other as each one is using different color correction strategy.

It is my experience that most of the users of color system do not effectively use correction program and just use the system for match prediction and routine quality control of incoming or outgoing material. Most of them stop using correction module or get frustrated. This may be because correction program is not effective or they find it complicated.

In case of paint industry, color correction program is the most useful program for reducing tinting cycle .One has to get the required target shade in one or two add. They need correction program more often in production tinting. As you know, situation in production tinting is just like “Fire Fighting”. It is a regular event.

In case of textile dyeing, one has to avoid re-dyeing or stripping of the color. Color correction process is very expensive process and one has to achieve the target color” Right First Time”. This is a real challenge when number of process variables make it difficult.

In case of plastic coloration, once the coloration process is complete, you cannot do anything. You reach a situation of “point of no return”. Nothing can be done as we do in paints or textile application.

Generally, correction programs are designed for different purposes. I am listing some of the important features needed for color correction module.

1)  Laboratory correction:  Positive correction or negative correction. In this case, in Laboratory, you can re-dye or re-assemble the batch with a new corrected recipe. It is possible to correct with negative correction i.e. you can subtract the colorant amount. The dye which has gone in excess can be reduced in new corrected formula ( Fig.2). In paints and textile application it is useful.

correction 1

Figure 2: Color Correction Program

2)  Laboratory Correction (Only positive add): As you cannot  subtract a colorant from the batch, you have to have only positive add. You can only add a colorant. It is called shading or tinting. This is mostly used in paint processing. In paint production or at Point of Sales facility , you need this program for getting a desired target if recommended formula does not work.

3)  Production Correction:  You cannot have negative correction. You have to correct the existing colored material without stripping. It is called small tinting or shading to achieve the desired tone.( See Fig.3) One can see the performance factor ( cf) of three dyes. Black  has behaved 2% higher,Red has behaved 0.01 % weaker and Yellow has behaved 9 % stronger. In this case , yellow is a measure problem because of which batch has failed. You can also see Fig 4 which is a different case where performance factors are completely out of range indicating the  incompatibility of colorants


Fig.3 : Production Batch Correction


Fig.4: Correction output with Performance Factors of Colorants – cf factors are our of range

4)  Interactive Add: In this option, you will have interactive dialogue with correction program. You will present the Standard and batch. It will predict the difference and display all color parameters such  L*, a*, b*. DE etc., You will look at these parameters and make your own guess and ask the program “What If ?“. That means you will ask the program to predict what will happen to batch if you add or subtract any colorant or colorants .That means, if you add any colorant, what will you achieve? You can suggest the amount of colorant and computer will do iteration and predict what will happen after using your suggestion. You can add one, two or three colorants simultaneously and it will predict DE for your guess. It is called “Colorist -Computer” Interaction. It is a powerful technique for any experienced colorist. If you are not an experienced colorist, you can also optimize the colorants and program offers you optimum solution.

5)  Adding Fourth Colorant: One can also add fourth or fifth colorant and see whether it gives better correction. Sometime, you need minor or small shading for achieving the desired tone. This flexibility of adding a new colorant is good but may create  problem of  metamerism.( Fig.5)  You can note that fourth colorant Yellow Oxide is added in the correction. One can select a colorant and try to fix the required color property such as redder/greener, yellower/bluer or lighter/darker by using “FIX “tabs such as L,a,b, C and h. One can also do “Manual” correction using manual tab. One can also “Zero” the colorant. You can look at L,a,b plot and see how color is moving towards standard color. One additional facility is given by which you can select the colorant and press “Fine,Medium or Coarse” buttons and do addition or subtraction of colorant. At the same time watch the L,a,b plot and see how you are reaching the target. This is very effective tool for correction of a batch.


Figure 5 : Add new colorant for tinting with different options

6)  Manual Mode: In this program option, one can correct the formula by selecting manual mode (colorist – computer dialogue) by opting for fixing L*, a*, b*, C* and h* values. This is a useful option for fixing preferred chromatic value(Fig.5)

7)  Hard correction: Hard Correction is ideal for lab or production correction when initial batch recipe is far from standard. ( Fig.6)


Figure 6: Different Correction Option : Hard,Soft,Super Soft, Optimize

8) Soft correction: Soft correction is used for those recipes, which are not far from given standard.

9) Super soft correction: Super soft correction is used for preferred tint.This is useful for whites and black.

10)  Optimized correction: Optimized correction is based on mathematical automatic correction program, which uses least distance travel approach.

11) Performance Factor: This Correction Program gives performance factor of colorant in a combination. It computes performance factors of colorant by looking at concentrations of colorants in standard and batch. It indicates, what has gone wrong? Is colorant in combination behaving differently? That means, for example you have added 3 % of colorant, but program sees only 2.8% or 3.2% colorant. That may be due to incoming lot of colorant used in production is weaker or stronger in strength or it may be that in a process you have selected, colorant which  is not diffusing well in textile application  or dispersed well in paint application or colorant pick-up in combination is different ( Colorant -Colorant interaction ).It also indicates development of color yield in isolation or combination. One can easily determine the incompatibility of colorants. You can see from Fig.7 that correction factor compensates the formula. Output indicates that  reflectance curves are not perfectly matched resulting into metamerism. ( DE is 1.2 for D65 and DE is  0.6 for A)


Figure 7: Correction Factor based on performance of colorant

12)  Graphic Additions: In this correction program option, you can see  L, a,b or L ,C, h graph with your tolerance circle. Standard and your batch are located on your graph along with three colorants in combination. You can graphically add or subtract colorants till you reach the tolerance limits . This is the most innovative correction program, I have ever seen. This is very useful program. You see standard and Batch on L, a, b or L, C, h plot along with three dyes and you can graphically add the component till you get very close match. This innovative and powerful program helps you to learn coloring.( Fig.5 )

Military Colors: Olive / Khaki colors

In Olive or Khaki shades, one has to always use correction program for getting desired tone. Generally,  if you add the fourth dye for shading which results into metamerism. One should always use tri-chromatic combination and never add the fourth dye.

Many times mixture dyes are used such as oranges, browns, olive , blacks.  Dyestuff manufacturers recommend many mixture dyes such as oranges, olives, browns etc., if you have three dyes in combination and in this combination, you have one or two mixture dyes, you will end-up with five or six dyes in combination, naturally it will result into metamerism. If you look at reflectance curves, you will notice more than 4 or five peaks and if reflectance curves are not perfectly matched that will result into metamerism. (DE for D65 and DE for A will be different).

It is observed that when you use two colorants of same hues such as orange and yellow or two blues of different tones, you face problem in correction as colorants are incompatible. This is mainly happening because of the use of two colorants of similar hues ( Two yellows or Yellow and Orange Dye). Problem of Khaki and Olive is quite complex.  It may be because you are using two dyes of similar hues.  One should not select such combinations where two colorants of similar hues are used.

Correction for Black and Grey

Black is not black. You may be looking for  preferred tone such as redder black or greener black. You may have to tint it or shade it with a new tint colorant.   Many colorant manufacturers offer black colorant which is generally a mixture dye – a combination of two or three colors. Ideally speaking, you can get a black from three pure red, blue and green colorants. One can always select a tri-chromatic combination. You will face minimum problem. Similar situation will arise in case of grey colors. Always obtain reflectance match and never add fourth colorant.


Correction of white is always a problem. Fluorescent Brightening Agents (FBA) are used for enhancing the whiteness of the material. One has to tint the material with FBA. Proper selection of  FBA material and its accurate and optimum concentration is very critical. One should quantify  and obtain its performance with  with concentration as K- M theory is not very effective for FBA.

TIPS for correction program

You must remember that color correction program is not effective because of reasons given below:

( I am giving listing for textile application.Similar problems can be listed in paints application and plastic coloration)

1) K-M theory is based on linear relationship of dye absorption and concentrations. Some of the dyes do not behave linearly. When one looks at the curve of (K/S) Vs. Concentration, one can find the change of low slope at low concentrations and high concentrations (<1% & >2%). Such behavior brings inaccuracy in match prediction and correction.( See Fig.8). You can look at colorimetric data of Blue colorant. Ideally speaking ,strength per unit concentration should not change. It is changing considerably indicating  that dye stength is not linear. The slope curve of log K/S Vs Log C also indicates that it is changing.


Figure 8 : Reflectance data of Blue Colorant with Different Concentration
K/S Vs Concentrations
K/S per Unit Concentration

2) Recipe calculation is based on primary dyeing, using several different concentrations of selected dyes. If primary dyeing data is not proper, you will face problem in correction as same data is used for correction strategy.) The accuracy of primary calibration data determines the quality of the color correction.

3) One has to have highly accurate and repeatable dyeing. This is mainly experimental error if dye behavior is not  linear.

4) In most cases when recipes are dyed under different conditions or on different substrate than primary dyeing, unacceptable color differences are obtained. Substrate correction factor is related to dye pick-up of substrate or pre and post treatment of substrate, which is used for dyeing. A simple substrate correction factor based on strength of dye will exist or statistical correction factors are to be obtained for each substrate.

5) Traditional color recipe calculations assume that dyestuffs, when mixed, behave the same way as used in isolation. Interactions between dyestuffs are not taken into account and lead to inaccurate color recipe.Dye strength/concentration relation may be linear, when dye is used in isolation. As soon as dye is used in combination (with one or more dyes), dye strength/concentration relationship is dramatically changed and many times not predictable. In such cases, one has to study the dyestuff behavior both in isolation and in combination and determine the statistical behavior for determining the perfect correlation factor.

6) Dyestuff behavior is based on dye-fiber interaction and dye-dye interaction. By keeping substrate constant one can find the correlation factor and apply the same for refining the prediction of the recipe.

7) Lab and Production correlations are related to process parameters and one has to obtain correct correlation factor. This can be established by collecting statistical data of lab and production recipes. The systematic analysis of final production recipe and initial lab recipe is carried out by using colorimetric data.

8) Effect of process parameters such as dye/ liquor ratio, pH, time-temperature, speed of operation etc., are to be determined and quantified for process standardization.

9) Standardization of dyes (Strength and chromaticity quantification) and proper selection of dyes for a given hue is to be done based on tri-chromatic combination.

Color correction program is the important tool for any colorist and considerable  savings can be obtained by effective use of this program if proper correction strategy is used.

Dr Narendra S Gangakhedkar

WRA COLOURMATCH : Web based color match service

February 18, 2013



Internet Based Color Match Service From Wool Research Association

Wool Research Association (WRA) is one of the leading textile research Institute in India located at Thane near Mumbai. They have carried out pioneer research work in the field of color science and its applications in textile. In eighties, they have developed computer color matching software and offered color match service to woolen industry in India.

Mr. M K Bardhan, Director of WRA , once invited me for conducting a training program on color science and its application for newly joined scientists working in color laboratory. After the program, he asked me,” What new can be done in the field of computer color matching which will be useful for small and medium dye houses in India as they cannot afford costly color systems?”. He told me that there are many small units in woolen industry which are in  need of  color match services.He wanted to offer color match service to WRA members having small dye houses. During the discussions, I suggested him the use of Internet technology and low cost affordable color measuring instruments.  He liked the concept and asked me to work on this project as a  color consultant.The project of internet based color matching system for small and medium dye houses was  started by him. Smita Honade and Aniket Bhute, WRA Scientists are working on this project along with other Laboratory staff. Dr C W Acharya, Assistant Director is the head of the team for co-ordination and administration. I got associated with this project as a consultant  and we developed “WRA COLOURMATCH ” system based on internet technology.

The cost of Computer Color Matching  System is very prohibitive for small dye houses as return on investment takes a long time. Main components of any color systems are spectrophotometer, PC  and color matching software. Preparation of database requires very good Laboratory facilities.Most of the dyeing units are not equipped with good laboratory facilities and color technology experts are not available to handle the color technology problems. Taking this into consideration, WRA  developed  a very simple solution for small dye houses. The main features of WRA color match services  are:


Dye House User will just require following  two things:

1) They have to  buy  a low cost hand-held spectrophotometer  for measuring target color.

2) They have to have Internet access to WRA website for getting  instant formula for any target color.

System is very simple. Just Click a button on the portable color spectrophotometer, and input the  reflectance data  into a web-page. The custom formula is just another mouse click away.

It is Internet based technology and there is no software to install, updates to worry about, or hardware maintenance of instrument. WRA has created  a huge database of all dyes used in dyeing.  Different substrates, different class of dyes and different dyeing processes are considered while preparing accurate database. WRA  laboratory is equipped with latest dye dispensing system and dyeing machines. Calibration dyeing database  is generated with utmost accuracy. Small Dye Houses will not be required to spend time and money on developing this huge work on database preparation.

Dye House will save 15-20 % cost of dyes as they will get low cost and least metameric matches.

Exporters will get correct matching with no rejection.

Time of matching will be saved as it will be instant color match with least metamerism and lowest cost.


  1. Place the sensor on the colored surface and click.
  2. Measure the reflectance  values of the target color,
  3. Connect to the internet and enter the numbers, and get custom formula.

How it is achieved by WRA?

Today, computer color matching systems available in the international market are very sophisticated and new generation spectrophotometers and color software are available. The systems are quite expensive. There are number of Indian color systems developed which are equally good.Taking this into consideration , we were not interested in developing or writing a new color matching software. We wanted to use established color match software and integrate the same  with Internet technology for web based application. We invited all the color system suppliers including Indian color system manufacturers. Because of commercial reasons, leading international suppliers did not agree to offer match software for internet  integration. Similarly, Indian color system manufacturers did not participate in this  program as they have to  convert existing software and make it compatible for internet applications.The Match software being the main component of the project, we were stuck-up. We had no alternative but to rewrite the color software for internet integration. Meantime,we identified  the color software developer, Mr. P Ravichandran who is textile dyer  and color software developer. He  has written color match programs which are  known as Pravin Color System (PCS). We evaluated his software package extensively by matching number of shades and found that color matching program written by him is  excellent  and it gives very good results. His color software was  found  suitable but it was not possible for him to integrate  it with Internet technology. For web based application, additional conversion program was required. WRA  entered into agreement with him and asked him to rewrite the Match module required for web application. This development and integration  work was carried out  by  him for WRA project. This is how WRA Colourmatch is developed and is now available to WRA Users.

Next step was to decide on color measuring instrument which is low cost and affordable  to WRA users. After studying different portable instruments, we decided to opt for X-Rite i1 Pro spectrophotometer which meets all the requirments.

Main mother system consisting of X-Rite i7 Spectrophotometer and PCS complete color software is installed at  WRA Laboratory along with a daughter color system consisting i1 Pro with match program module of PCS .   Database is prepared by using both the system. .WRA Laboratory developed wide range of database taking into consideration Substrates- Class of dyes- and Dyeing processes. Actual user’s processes were studied and incorporated into database which is now  a real representative of user’s dyeing environment. Master database required for color match prediction is prepared in WRA laboratory and uploaded to WRA Colourmatch Server. Time to time, database will be updated by WRA administrator. The System is designed very user friendly and interactive. At the user end, user has to measure the custom color. He has to select the set of dyes and click for the match. He instantly gets the  low cost and least metameric recipes. He can select from the alternate combinations. He can look at the reflectance curves of the standard and predicted recipe and judge for the metamerism based on spectral curves. WRA use’rs are spread all over India and they can access the color match service 24X7. Special –exclusive -custom made database will be made available to individual user’s based on Substrate-Dye-Process combination.

 X-Rite i1 Pro is used for color measurement by the user .


Fig.1: X-Rite i1 Pro


Each user is given a User ID and Password. User can access the WRA Web site – WRACOLOURMATCH . He reads the custom color as shown in Fig .2


Fig.2: Color is measured by i1 Pro and stored in Standard file. It can be retrieved by name or number.

User/Operator Clicks the button of “Formulation” after measuring the Standard. He selects the data file of dyes to be used. He can select all the dyes in a set or select dyes of his choice with select/unselect option.( Fig.3)


Fig.3: Selection of Dyes from a set of Dye

As soon as dyes are selected, he has to click “Formulate” button and number of recipes appear giving the cost of recipe and Index of metamerism. ( See Fig. 4) One can select the recipe and look at reflectance curves of the  standard and predicted recipe.


Fig.4: Match Predicted Recipes giving cost and degree of Metamerism. Reflectance Curves of Standard and Predicted Recipe are are also displayed.

Quality control program which gives color difference , color strength  and whiteness/yellowness indices is also part of the color system. Pass/Fail program is  useful for quality assurance of incoming dyestuff and out going materials. This is how it offers the complete solution to small and medium dye houses.

Those who are interested in WRACOLOURMATCH  services can contact :

Director, Wool Research Association , P.O. Sandoz Baug, Kolshet Road,, Thane- 400607, Maharashtra
Tel- 91-022-25314294/ 25868398 , Tele Fax 91-022-25868365
Email: wra@wraindia.com

Use of CIE Chromaticity Diagram for Quality Control of Colorants and Prediction of Color Recipes

February 12, 2013

Understanding of color is still not complete.Artists talk of color in terms of Hue, Value and Chroma or Tint, Shade and Purity of color. Munsell was the first who specified color in terms of Hue, Value and Chroma. Ostwald described color in terms of Tint, Shade and Purity. CIE  defined color in terms of Tristimulus Values( X, Y, Z) and Chromaticity Co-ordinates (x,y). CIE also defined additional terms such as  Dominant Wavelength  and Purity. CIE  Colorimery has further improved  our understanding of color. We will try to understand CIE System which is generally  illustrated  by CIE Chromaticity diagram. It offers us a lot of information and in industrial application, we do not go into details as it  looks  quite complex and mathematical in nature. In this blog , we will try to find out its use for quality assurance of colorants and how to obtain colorant formulation of target color.

Purpose of colorimetery is to express color as numerical values and colorimetry is nothing but a technique of color measurement . We therefore have a Triplet, composed of

1) Light source(S),

2) The Object(%R) and

3) The Observer’s color sensitivity functions – ( x.y.z).

Color = f (S,% R, x,y,z.)

Color can be expressed in three numbers (X,Y,Z) which is known as tristimulus values.The calculation of  tristimulus values  for any given colored object requires the multiplication of its spectral power (S) at each wavelength times the weighting factor from each of the three color matching functions (x, y, z) and reflectance of the sample (%R ). Summing these contributions gives three values called the tristimulus values( X,Y,Z) see Fig. 1. Color is described or specified  in terms of three numbers. See Fig.2. Chromaticity Co-ordinates are defined as

x= X/ (X+Y+Z)  and

y = Y/(X+Y+Z).

Chromaticity diagram  is plotting of x vs y. This diagram represents the mapping human color perception in terms of two CIE of parameters x and y. ( Fig.3) All the spectral colors are distributed around the horse shoe shape color space and is called CIE chromaticity diagram. The boundary represents maximum saturation for the spectral colors, and the diagram forms the boundary of all perceivable colors.

computation of X,Y,Z

Fig.1: Calculations of Tristimulus Values

Color specified as X,Y,Z

Fig.2: Color as Numbers – Color specified as Tristimulus Values ( X,Y,Z)

Dominant Wavelength and Purity defined using CIE plot

Fig.3: Dominant Wavelength and Purity defined using CIE plot



One can easily find out dominant wavelength and purity by locating the color on CIE plot after obtaining CIE Chromaticity co-ordinates (x,y) . If you join the two points ( C0-ordinates of illuminant and Co-ordinates  of color (x,y)and extend the line  which touches the CIE spectrum locus indicates the dominant wavelength of that color and purity is defined as the ratio of  a/(a+b). Dominant Wavelength and Purity are two most important parameters of any color.

In CIE System, we have to get the Dominant  Wavelength which can be easily correlated to Munsell Hue.  CIE Purity value can be easily correlated to Munsell concept of Chroma. CIE Y value is correlated to Munsell Value.As we know, CIE system is a physical System and Munsell System is psychological visual system. We can easily correlate the two systems, which gives us psycho -physical correlation.Correlation of CIE System with Munsell System is illustrated in the diagram.(Fig.4)

Dominant Wavelength and Purity are the two parameters derived from CIE chromaticity diagram.  One should note that CIE System is independent of human observer while Munsell System is a real visual system.

Every color is having a dominant wavelength and purest color lies on the boundary of the plot.( Fig. 5 & 6) One can characterize every colorant ( dyestuff/pigment ) by its dominant wavelength and purity. If you plot coordinates of colorant  with different concentrations on CIE diagram, you will get information on behavior of  colorants.  Red color ball shown in the following chromaticity diagram (Fig.6) , is having dominant wavelength 630 nm . If the ball is closer to spectrum locus point , it is 100 % pure color. Most of the colorants are not 100 % pure. Getting such type of colorants is difficult and it is still a challenge for chemists to get such colorants.  CIE Color triangle illustrates how achromatic colors / different illuminants are represented in CIE diagram.(Fig.5).

Color is specified as three numbers(X,Y,Z). However, one cannot get complete picture of what color you are talking. In order to have correct idea of a color , we should look at other color numbers such as dominant wavelength, purity, L,a,b,C,h,DE, % R values, Color Difference (DE) in at least two illuminants ,  K/S value at R minima for strength etc. One can also use conversion equations and obtain corresponding R,G,B values  and  C,M,Y,K values. All these parameters will give you total picture of color.  When we talk of colorants( dyes or pigments) , we are specifically concerned with color strength and color difference or chromaticity. We do not understand the importance of dominant wavelenth and purity. If we are comparing two colorants, we must take into account the role of dominant wavelength and purity along with color strength and chromaticity or color difference as it is and color difference after adjustment of color strength.If dominant wavelengths of standard and batch are not same or there is a difference of 2 to 3 degrees , then it is sure that there is a hue shift between the two samples which will create problem in color formulation. Similarly, if purity of two samples is different, it may create problems in color matching. Hence , for quality assurance of colorants  , one must consider the role of dominant wavelength and purity.

CIE Illuminants are located on CIE diagram

Fig.5: CIE Illuminants are located on CIE diagram

CIE Diagram

Fig.6: CIE Diagram

Dye concentrations are plotted on CIE Diagram

Fig.7: Dye concentrations are plotted on CIE Diagram

Three colorants with different concentration

Fig.8: Three colorants with different concentration

In Fig 7, we have plotted the different concentrations  of the dye using chromaticity co-ordinates of each concentration, In Fig 8 , three dyes with different concentrations are plotted. One can see from these plots ( Fig.7 & 8) that as concentration is changing the dominant wavelength is shifting. It indicates the hue shift. Purity of color is also affected. Good colorant should not show any change in dominant wavelength if the concentration of colorant is increased . Such type of colorants create problems when they are used in combination. Change in dominant wavelength means change in  hue. Hue is changed considerably.This should not happen in case of good colorant as purity is also affected.

L,C,h Diagram and CIE Chromaticity Diagram offers same information

Fig.9: CIE L,C,h  Diagram

If you look at L,C,h diagram (Fig.9) ,you can easily see that small change in hue angle makes a lot of difference. Our eye detects hue change first. Small changes in hue difference are not acceptable. One can derive similar information from CIE Chromaticity diagram. Dominant wavelength in CIE diagram and Hue angle change in CIE L,C,h diagram indicate the  same phenomenon.

Colors on CIE Diagram. Achromatic colors on CIE Plot

Fig.10: Colors on CIE Diagram. Achromatic colors on CIE Plot

In this CIE Diagram, different colors are plotted ( Fig.10). Achromatic colors are also shown. All possible colors are shown in this diagram. However, one cannot obtain all these colors in real life as color gamuts are different for different applications. In case of  addition of light colors, it is possible to get such color gamut. In subtractive color mixing , color gamut is limited.

One can easily obtain colorant formula , if we plot the chromaticty co-ordinates of each colorant. Theory of Tri-Chromaticity is derived from this. For matching a color , you have to have at least two or  three colorants.

How to obtain color formulation from CIE Diagram

Fig.11a: Prediction of Color formulation from CIE Diagram

One can compute colorant formula from CIE Diagram

Fig.11b: One can compute colorant formula from CIE Diagram

One can see color triangle formed by three colors  R,G,B . We can obtain all possible combinations for any target color. C1 and C2 are two colors from which we can get color C3.( Fig.11a). One can see from this CIE diagram ( Fig.11b) that target Color ,T can be obtained by colorants J and H , C and D, or F and G.The pairs shown in the figure CD, FG and JH can produce the color T if combined in right proportions.  It is found that many different combinations of light wavelengths can produce the same perception of color. This is how one can use the CIE chromaticity diagram for obtaining trichromatic color formulation. One can have number of combinations based on different colorants. Many different combination of colorants can produce the same color. One can easily find out the proportion of different colorants. Theory of tri-chromatic  colorant formulation is based on this chromaticity diagram. Some of the earlier works on predicting colorant formula is based on this approach. When I started working in this field, I ordered a big chart of  chromaticity diagram for our Laboratory and plotted chromaticity coordinates of  all pigments used in paint making and obtained all possible formulation from chromaticity plot. It worked very well. It has given me good idea of selecting the pigment combination based on theory of triangulation and finding out alternate combinations. One can also find out suitable  substitute pigment very easily .


Fig.12a: RGB TRIAGLE. and Achromatic Colors- Light sources changing hue as color temperature is changed



One can easily obtain colorant combination based on three colors ( R,G,B) . This is true when you add light colors ( Fig.12a and b)). In case of colorants , you will need three colorants forming a triangle. Color gamut will depend upon the size of triangle. For example, color gamut for polyester disperse colors will be different from color gamut of reactive or vat dyes of cotton. Similarly, color gamut of organic pigments will be different from that of inorganic pigments used in paints, plastics or inks.One can easily see from this diagram that one can match any color in the triangle formed by the three colors, blue – green – red. The solid line outline encompasses all hues which are perceivable to normal human eye. The horse shoe shaped curves contains the spectral colors. The straight line at the bottom is the line of purples. The combination of light wavelengths to produce a given perceived color is not unique.One can plot the co-ordinates of  all colorants on this diagram and look at the color gamut formed by colorants. One can easily determine the proportion  of colorants required for getting a match for any desired color. One can also look at the color gamut based on colorants available.Colors beyond the triangle cannot be achieved in reality.One can also see how illuminants are showing hue shift indicating that light soureces are colored as color temperature is chaged(See Fig 12a)

Color Gamut

Fig.13: Color Gamut

One can see the color gamut of CMYK and Hexachrome system ( Fig.13). Similarly,one can plot color gamut for different systems such as disperse colors for polyester, reactive colors for cotton or color gamuts of organic /inorganic pigments used in paint or ink system. Perceived colors can be easily seen in chromaticity plot. One can easily find out colorant combinations from this chromaticity plot Fig.14).

percievable color in cie

Fig.14: Color Triangle

Dominant wavelength and purity are  characteristic  properties of any colorant. Color Gamut depends on the  range of colorants available . If there is shift in hue because of change in concentration of colorants, dominant wavelength changes. Such type of colorants do create problems in color matching. Color gamut for different systems are different. For example,  colors which are obtained for cotton-reactive dye  system cannot be obtained in cotton- vat systems as color gamuts are different.One can effectively use CIE diagram and  learn a lot from the information obtained from CIE plots. One can easily formulate colors from CIE plot. Generally, Kubelka-Munk theory is used for match prediction. A sound logic based on chromaticity diagram can be tried for colorant formulation. One should remember that tri – chromatic combination will be always better for consistency. One can plot the dyes co-ordinates on CIE chromaticity diagram and find out three dyes which are forming a triangle  and given recipe co-ordinates are lying at the centre of the triangle. One can have any number of tri – chromatic combinations depending upon the dyes forming different sets of triangles in CIE chromaticity diagram. If you select the tri – chromatic combination, generally you face minimum problem.

Recently, formulation programs are written based on this logic. In paint system, color cards ( 1500 shades) are measured and (x,y) values are computed. For each color , established formula is known. From color gamut of this system and known formulations, one can easily  predict the formula for any given target color . This approach is different from K-M theory and it works very well for white based paint system. One can also effectively use this approach for ink formulation.

Color is fully described by color terms such as X,Y,Z, L,a,b, C,h, Dominant Wavelength,Purity,% R values, K/S values, Color Strength, converted values such as  R,G,B,C,M,Y,K ,DE-Color Difference between Standard and Batch for at least two illuminants for detecting metamerism and spectral curves. One should look at all these numbers and make assessment of color using CIE mathematics.

Note: Some of the illustrative diagrams are taken from published literature. I acknowledge with thanks for using them in this blog for explaining the points.

Instant Color Matching for Paint Dealer Shops

February 11, 2013

Internet based color matching at POS

There is innovative development   in POS color system based on Internet technology (Benevue 2009). It is not based on normally used conventional K-M theory for match prediction. In this new POS color system, one needs a color sensor and an access to web page of service provider. There is no need to determine optical properties (K and S coefficients) of the bases and colorants. One has to just supply the existing formulas of the fandeck colors in electronic form and service provider’s software will take care of matching of any given custom color. There is secrecy of the software package as they do not want to disclose the mathematics of color matching. It is mainly database driven.  For every color, there is a formula. Every color is having unique color specification such as X,Y,Z or L ,a,b  or R,G,B .This is correlated to established color formula and color bases and white base used for matching. Once you have large number of colors covering the full color gamut and you have the established formula bank, you can predict the tint formula for any custom color by using database and powerful mathematics. Benevue has done lot of work in this field and author knows this product development and has worked on it extensively.Main features of this new system are:

J & N 9

Fig.1: Color Reader – Low cost, very accurate and specially calibrated.

1)      Zap your inspiration: Take your color reader and simply measure the desired custom color in terms of three numbers (R, G, and B).

2)      Log on to your internet website by entering  your user name and password password ( See Fig.2)

J & N 16.10

Fig.2: Enter your User name and Password on Service Providers web site

3)       You will see various options available in the menu – book formula, closest color and tint by name etc.,( Fig.3)

J & N 14

Fig.3 : Different Options to select – Book Formula, Closest Color and Tint by Name

4) You enter the three  color values of custom color (See Fig, 4 ), and select the desired option say,”Book Formula / Tint by Name /Tint by Reading”  ( See Figures : 5,6,7)

J & N 14

Fig.4: Enter Three Color Numbers ( R,G,B) of Target Color read by the Color Reader

J & N 16.11

Fig.5: Book Formula

J & N 13

Fig.6: Formula Option -Tint by Name

5)      You will get the exact color formula  by selecting the option ‘Tint by reading’( See Fig .7 )

J N 15

Fig.7: Formula – Tint by Reading

6) Use the Formula to mix: Computer instantly gives the tinting formula which can be send to automatic dispenser or one can mix it manually.

Number of fandec colors and their formulae are stored  on central server along with matching software and one can get the formula by using the name of color in fandec or any other options.

Author has worked with Benevue color management system and introduced the same to a leading paint company in India and established this technology at number of paint dealer shops. Results are extremely good.  Illustrations mentioned here are the actual data obtained by the author who has matched hundreds of pastel and saturated colors using Benevue Color Management System. It is a unique system offering low cost, internet based color matching solution.

Color Readers : There are  three options available. 1)  Pocketspec Spectro  2) Colorsavy Color Reader which is modified and specially calibrated for this system and X-Rite i1 Pro. These are low cost instruments but need calibration procedure recommended by service provider of color software.

Conventional CCM Vs. Internet based POS

1 In conventional CCM system, daughter system at the Dealer’s shop needs experienced operator and database update is to be carried out from the instructions of mother system.

2 In internet based Dealer shop system one can update it automatically as it is on central server.

3 In Internet based color management system, centralized database of Fan deck, Formula Book etc., is on the main server which is instantly available to any paint dealer shop on the Internet. Dealer need not worry on updates.

4 Internet based system is equipped with instant use of Formula Book, Closet Formula, Formula for any product line, formula for any base / any tint base.

5 Central server is having an ” Eye” on paint dealer shop and one can get all the information about the usage of the dealer, number of new custom colors matched, new formulas found, competitors colors popularly used, regional sales, dealers sales etc.It offers unique data mining facility which is extremely useful for sales/marketing analysis.


1) Benevue (2009) http://www.benevue.com

2) “Colour measurement: Principles, advances and industrial applications”, Edited by M L Gulrajani, PART 2,  COLOUR MEASUREMENT AND ITS APPLICATIONS, Chapter on “ Colour measurement of paint films and coatings” written by , N S Gangakhedkar, Compute Spectra Color Pvt. Ltd., India ,Woodhead Publishing Series in Textiles No. 103 .(2010)