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In order to understand the colour we have to know, how the colour is perceived. The perception of colours [1] involves the interaction of three elements. (i) source of light, (ii) an object and (iii) human eye.
Colour can be broadly defined as the physio-psychometric effect on the brain of an observer from reflected wavelength of an object, when that object is viewed in presence of a definite light source.
Colour theory meant a Standardised scientific method with specific mathematical/empirical formula with arrangement of incidence of light/standard illuminant for absorption and reflection of the colour on and from the object and then detecting folowed by measurement of colour value specific reflactance or any other quantified values to record and communicate colour information for reproducibility and matching.
As per CIE definition 845-02-18: (perceived) co
Human Perception of colour usually appear to describe a colour in terms of amount of RGB (Red, Green and Blue) sensation of human eye as an additive colour mixing system (as shown in Figure 1) distinguish among qualitative and geometric differences of colour perceptions by its predominating Hue (predominating Reflected wavelength observed), Value (Light or Dark i.e. White or Black respectively) and chroma (Strength or Concentrations of Coloured mol.) [1] with/without associated brightness/dullness and uv absorption.
Schematic display of colour observed from RGB primary colour stimuli with standard illuminant by a standard observer /detector.
Thus, Colour of any object can be considered as an physio-psychological illusion of reflected radiation / visible light from a substance/object after incidence of light on it, which is to be detected in exact quantitative terms by amount of RGB in it (Figure 1), while, colorimetry is the measurement and evaluation technique of colour value in any quantifiable terms by which this physio-psychological sensation of our eyes can be converted to the actual physical measurement of colour values either in solution or in solids in some sensory values of primary colours.
If any one want to buy a skirt or a pair of slacks to match a jacket, one cannot match the colour by memory — he/she has to take the jacket with him/her to match it visually by judging colour by eye measurement in the store itself. it may happen that in some cases, the store light is insufficient and faulty matching by eyes results, So, one has to match it also under standard and sufficient incandescent light in the dressing room and and also in the outdoor sunlight too.
Three fundamental components of understanding or measuring or matching any colour:
light sources /standard illuminant
objects / samples illuminated by standard light
observers /detector to record colours reflected from it
Most Important and commercially useable Two of the major Colour quantification systems are:
Munsell Colour Theory -hue, value and chroma
The CIE Theory of Colour -Tristimulus values (X, Y and Z) and CIE L*, a*and b* values
The CIE Theory of Colour −1931 updated in 1976 [1.2] is in wide commercial use for textile’s colour communication and hence it has significant importance in apparel sector and is described below.
The Commission Internationale de l’Éclairag e (CIE) has recommended x(l), y(l), z(l) for lÎ [360 nm, 830 nm] in 1 nm steps for distinguishing colour based on tristimulas values, which are well accepted/.
Over a wide range of conditions of observation, many colour stimuli can be matched in colour completely by additive mixtures of three fixed primary colour stimuli (RGB) combine linearly, symmetrically, and transitively and may be expressed as X (stimuli of Red Primary), Y (stimuli of Green primary), and Z (*Stimuli of Blue Primary) as three coordinates called Tristimulus values (X, Y and Z) or stimuli of any colour observed under standard illuminant under standard detector / observer, based on reflected contributions of R G B primaries from any object (Figure 1) having spectral sensitivity of RGB primary stimuli (as shown in Figure 2a) and actual Tristimulus values of any object (X, Y and Z values, as per formulation shown in Figure 2b).
(a): Spectral sensitivity of human eyes of RGB primary Stimulli and (b): Resultant actual measurement of reflectance values and corresponding Tristimulus values of any object.
Thus, a monochromatic colour stimulus (
where Rl, Gl, and Bl are the spectral
Consequently, the
a: CIE 1931 chromaticity diagram showing b: CIE 1931 chromaticity diagram all predominating visible hues at 380-700 nm (coloured) showing x and y coordinates.
Hence there is no need to plot a three dimensial x,y and z diagram, rather the 2 dimensional chromaticity coordinate plot (Figure 3a or b) is sufficient to get x,y & z values from x vs. y plot of 2 dimensional CIE chromaticity diagram [1, 2, 3].
CIE 1976 lightness/darkness is represented by,
CIE-L* a* b* system of colour difference plot to determine ∆
Example of metameric match under two different illuminant (day light and Fluoroscent light conditions.
Chroma, (psychometric chroma) values in CIELAB colour space [1, 2, 3] was calculated as follows:
Where, C*1(ab) and C*2(ab) are the chroma values for standard and produced sample.
CIE 1976 metric Hue-Difference (∆H) for CIELAB system [1, 2, 3] was calculated as follows:
Total Colour Differences [1, 2, 3]:
As per Kubelka Munk Equation [1, 2, 3]. Surface colour Strength (K/S value) of Coloured flat surface is:
Where K is the coefficient of absorption; S, the coefficient of scattering; and Rʎmax, is the Reflectance value at maximum absorbance wavelength (λmax) and CD is the dye concentration and α is the constant.
For use mixture of colourants to obtain a compound shades on the surface of textiles or similar substrate, as K/S is additive in nature, it can be represented as follows:
Moreover, plot of dye concentration Vs K/S value is linear in relation and is easier to predict for any unknown concentration of dyes, while plot of Reflectance vs. dye concentration is non linear in relation and is difficult to predict and hence K/S is an important surface colour measuring criteria of textiles, against application of increase or decrease in dye concentration on same or similar fabrics.
For coloured textile materials, it may be presumed that dye molecules are not contributing to change in scattering and therefore K integrated over visible wavelength is the total sum of absorption of dyestuff and textile substrate (so, if substrate is not changed, scattering is not changed). Therefore, surface colour strength i.e. K/S value is directly proportional with concentration of dye molecules and the scattering value of the dyed textile sample is not dependent on the concentration of dye stuff (but that is not true for the case of pigments in paint or binded over textile substrate with binder chemicald and fixed on the surface of the materials). So, for textile substrate, it is single constant theory of Colour Matching applicable for all textile materils.
Hence, for any textile surface, for the particular dyed/coloured textile sample (Fibre, Yarn and Fabric construction and type and amount of surface deposited (coated or impregnated)finish remains un-altered), and scattering values remains constant always, if textile fabric used is not changed.
Thus higher is the K/S value, meant higher is the absorption value, meant higher absorption value signifying or indicating higher surface dye uptake, governed by following formulae.
Finally, reflectance Vs. dye concentration is not linear & is difficult to interpolate or curve fitting.
While K/S Vs. dye concentration is linear can be interpolated thus can be used in computerised colour measurement and matching software.
A colour match between two sets of samples means:
Colour of produced sample = Colour of given standard sample i.e. (XSL,YSL,ZSL) values of produced sample = (XSD,YSD,ZSD) values of given standard sample while X,Y & Z are the tristimulus value of produced Sample (SL) and Standard (SD) sample Also match may be predicted or judged [1, 2, 3] by (Reflectance)SL of produced sample integrated at 400 to700 nm = (Reflectance)SD of standard sample integrated at 400 to 700 nm or (K/S) SL values of produced sample = (K/S) SD value of standard sample, where K/S = α CD and K/S values (as per kubelka munk Equation [1, 2, 3]) as stated above), is:
For a ternary mixture of colourants/dyes to obtain any particular compound shade on textiles, three equations are to be solved as a function of dye concentrations of the colourants (1,2,3 or n) and have to determine tristimulus values or K/S Values obtained through reflectance measurement of samples to match. More over K/S value being additive and dye concentration vs. K/S being linear in nature, the resultant K/S value of a dyed sample (dyed with mixture of three different dyes (d1, d2 and d3) in respective concentrations (c1, c2 and c3) is represented by following matrix equations:
Where,
In practical ceases, the reflectance values of given standard sample at 400 to 700 nm are determined from given standard coloured solid textile fabric surface and the obtained results of reflectance values at different wave length in visible region are processed in computer aided colour matching software for matching
A textile match however should be ideally be an isomeric match i.e. match under all illuminant. But in actual practice, when two coloured sample show a match of colour under one illuminant may not match under other illuminantand this difference of match under specific two conditions of different illuminant is termed as illuminant based metameric match. Besides variation of illumainnat, there are other different types of metamerism for change of conditions of colour measurement, as follows, arised during colour matching under varying ambience of any one factor or others [1, 2, 3]:
Types of metamerism:
Colour matching is therefore based on to find a Least metameric match where, General metamerism index [1, 2, 3] is as given below:
Where ∆R = Difference in reflectance between pair of metamer samples;
The Metamerism-Index (MI) shows the probability that two samples will show the same colour difference under two different illuminants (represented by the first and second illuminant) or under two different instruments or under any two different conditions of colour measurements. CIE LAB i.e. LABD metamerism index [1, 2, 3] is represented as:
∆
When, MI (metamerism index) is low, the colour difference between the sample pair (standard vs. produced) is the more closer and similar, for different conditions of measurement even under different illuminants.
Reflectance Spectrophotometers are very effective instrument in measuring and recording colours of any solid substrate / textiles from its substrate. All measurements are done by CIE −1976 System [1, 2, 3], which is commonly used in textile and other colour related industry.
The accuracy of colour matching of textiles depend on the set of tolerance limits [1, 2, 3] for
Thus these colour difference data has many benefits to the dyers entailing how much it is darker or light, how much it is redder or greener or how much it is bluer and yellower, when the shades of two nearly match samples are compared. Thus, Human eye estimated perception of colour differences between two or more objects against any standard shade, can be quantified to numerical values of colour differences in terms of total colour differences (DE values) and also in terms of DL(light and dark), Da (redness and greenness) and Db (blueness and yellowness). This has made easier to match/compare colours of textiles of a nearly matched two dyed textile samples(Standard shades given vs. Produced shade) by determining what are the colour differences between the two, leaving behind opportunity by batch correction either manually or instrumentally [1, 2, 3] to help different dyers to add or substract particular colour to get better match.
The reformulation of batch correction issue for computing the incremental value of concentration of dyes by each iteration at each stage may be represented by the following matrix as follows [4]:
Photometry is the most common analytical technique used in measurement of colour in solution/solid in the laboratory. It is designed to measure the intensity of transmitted /reflected beam of light through the coloured solution/solid. Different types of instruments with Photometric principles are applied to the different ways of analysis of coloured materials /substrate/solution by different techniques [5] as listed below:
Where absorbed or transmitted light is measured:
Colorimeter
UV–VIS Absorbance Spectrophotometer
Atomic absorption spectrophotometer, and
Turbidometer
Where emitted light is measured: Flame photometry
Where reflected light is measured: UV VIS Reflectance Spectrophotometer
In analytical chemistry or in textile analytical chemistry laboratory, colorimetry based on UV VIS Spectrophotometer technique is used to determine the concentration of coloured compounds (analytes) in sample of a coloured solution or in solid coloured sample of textiles or leather or plastics or polymer film or any other chemical compounds” at visible spectrum of light (400–700 nm as VIBGYOR as described in Figure 6), is observed in the visible spectrum of electromagnetic radiation, emitted in the form of dominating wave lengths emitting VIBGYOR wavelengths ranging from 400 nm to 700 nm. Similarly UV Light /sunlight radiation usually is observed to have UV radiation of 180 to 380 /400 nm wave length, as UV-A, UB-B, and UV-C type.
Major wavelength from incident white light dominating at visible range.
UV VIS Spectrophotometer technique of colour measurement are done by following two principles:
UV VIS Absorbance Spectrophotometry: (for determining UV–VIS wavelength scan pattern of a particular coloured compounds/dyes and to determine concentration of pure coloured compounds/dyes (analytes) in sample solution(dilute solution)
UV VIS Reflectance Spectrophotometry:
This chapter mainly covers the basic principles of analysis of surface colour parameters vis a vis other appearance properties of the surface of solid textile materials and associated colour difference parameters by using Reflectance Spectrophotometer in terms of specific 1931 CIE and 1976 CIE formulae [1, 2, 3] for determination of all specific Surface colour parameters of textile materials, changes with or without different chemical processing and computer aided colour match prediction theories and practices [7, 8].
Reflectance Spectrophotometer is an human eye simulated UV–VIS double beam spectrophotometer instrument for measuring colour of solid textile surface under standard illuminant and standard observer with or without Uv Absorption included and Excluded to measure reflectance, surface colour strength and to compare the colour differences of two sets of samples nearly to match or unmatched/matched coloured samples and also for storing and analysis of database of colour values of different textile dyes applicable to different textile substrate and its use for computer aided colour match prediction at finger tips with specific allowable limits of ∆
In UV–VIS reflectance spectrophotometer based on measuring reflectance of the solid sample for measuring different colour parameters for quality control and colour matching purpose, there is tungsten light source, which acts as source of monochromatic incidence light and it falls on the opaque surface of the solid sample at a particular incident angle to reflect at the same angle for specular reflectance component and also reflects the incident light all around in diffused form at all angles for non-specular reflectance inside the integrating spehere. THere are specular component in and out arrangement with UV component in and out arrangement for specific requirement of setting ofv the instrument. Led detector situated in the inside circumference of the integrating sphere detects the total reflectance values at all diffused angles as well as at specific specular reflectance angle and the amount of reflected light intensity is measured and shown as the reflectance values of sample at different wave length. Finally from reflectnace values obtianed for any sample, it calculates other colour parameters as per CIE −1976 formulae [1, 2, 3] and other formulae as per software inserted/installed for it for the data processing in a suitable computer system for computer aided colour measuring and also for textile match prediction system using pre-fed data base of textile dyes.
Usually a double beam UV VIS reflectance spectrophotometer, the incident light beam is first split into two parts by a half mirror as two light beam called double beam. One light beam falls /passes on the sample mounted and the other light beam falls (for reflectance mode) /passes (for transmission mode) through a control sample panel. This system of double beam eliminates the problems of interference from control sample and normalises the variations in reflected /transmitted light intensity readings uncreasing accuracy of the instrument reading, as the final reflectance/ transmittabce/absorbance values are taken as the differences between the readings of two reflected/transmitted beams of light intensity recorded. The semicircular LED Detector inside the integrating sphere measures both the two reflected/transmitted light intensity alternately and gets its processed in computerised processor to give final reading. However, in some UV–VIS spectrophotometer, a second detector is separately installed to measure the intensity of the two beams separately. Thus, the major instrumental parts of an UV–VIS Double Beam Reflectance Spectrophotometer are shown in Figure 7 indicating the position of light source, diffraction grating, monochromator, sample cell/ integrating sphere, detector and integrator and computerised recorder. The instrument changes the light source from visible to UV light at about 350 nm by a mechanically moving mirror, as shown in Figure 7.
Schematic diagram of working of UV–Vis spectrophotometer.
The diffused reflection shows total effect of incident light including specular reflection in integrating sphere diffraction, which may be excluded by opening a port at particular angle without detecting the specular reflections in UV–Vis reflectance spectrophotometer and different types of solid samples with varying surface and texture show variation in reflectance values, effecting surface colour strength, as shown in Figure 8.
Schematic diagram of optical system of UV–Vis reflectance spectrophotometer.
Sphere Geometries of illumination and viewing in reflectance spectrophotometer [7, 8] is very important here. It is based on mesaurement of Reflectance of dyed samples of textiles. On a glossy surface there are mirror-like (specular) reflections and there are more reflections in the case of diffuse light sources. Figure 9 shows the effect of transmission mode and total reflection mode of integrating sphere of in UV–Vis reflectance spectrophotometer, showing provision of specular component inclusion and exclusion by keeping specular port off and on (close or open).
Schematic diagram of working of integrating shere type optical system in UV–Vis reflectance spectrophotometer.
Since the colour of the illuminant is white, specular reflections add white, with the effect of de-saturating the colour. Textiles or any non-metallic glossy surfaces look more saturated in directional than in diffuse illumination, while matte surfaces scatter the light diffusely — matte surfaces usually look less saturated than glossy surfaces.
Most of the textile surfaces are between glossy and matte and hence in reflectance spectrophotometer, diffuse illumination is provided by integrating spheres with provision of gloss traps /lid at regular reflection points to include or exclude specular/regular reflectance in instrumental set up. REflactance spectrophotometer Instruments with 45/0 and 0/45 geometry are less critical and give better results and accuracy. ASTM recommends [1, 2, 3, 4] use the geometry that minimises surface effects (usually the one that gives lowest Y and highest excitation purity) for partly glossy samples. 45/0 geometry gives rise to polarisation problems [9].
Colour Difference Index (CDI) [10] indicates the combined effects of different known individual colour difference parameters between any two samples when dyed with varying conditions of dyeing, indicating dispersion of colour value, to understand the combined effects of different dyeing variables by a single parameter. For application of same concentration of dye between two sets of dyeing under any varying conditions of dyeing like pH, taking only the magnitudes of the respective Δ
Higher the CDI value dispersion of Colour values are more widely dispersed and that variable become critical for reproducibility for such dyeing. So, Lower CDI value below 5.0, is considered as good.
The followings are the Standrad Illuminats [1, 2, 3] used in Reflectance Spectrophotometer, providing UV -Tungsten lamp for different illuminant with swift arrangement of Illuminnat -A to Illuminnat -D65.
20 standard observer (small area of view) and 100 standard observer (large area of view).
Computer aided Colour Match prediction system (CACMPS) [4, 9] is the combination of specific hardware and software for scientific use for measuring colour of solid textile surface for given sample as standard for predicting the dyeing recipe or formulation for the exact shade reproduction in a textile fabric sample to produce. Hence, this technique is known by names e.g-computer colourant formulation, computer recipe prediction, Instrumental colour matching system or Computer aided Colour Match prediction system (CACMPS) using reflectance spectrophotometer and associated computerised sytem for storing and analysis of data with specific software to predict colour matching of textile substrate. A colour matching computer system consists of the following three basic modules,:
Colour measuring instrument: A Reflectance Spectrophotometer with specific geometry of colour measurement, which expresses the colour in numerical form in terms of X,Y, Z or R or K/S values with
Computer hardware: Usually latest PC or Laptop based Computing and data analysis and storing system for data storing, analysing and processing for converting and comparing etc.
Specific Computer aided colour match prediction software with desirable Logic system for computer aided colour measuring /storing and analysis of colour data to convert into relevant information in terms of calculating X,Y, Z, R, K/S values and
So, Suitable Software is crucial in recording, analysing for colour measurement and matching and for comparing a pair of nearly matched textile dyed/coloured samples. Samples should have the same type of fabric, same surface finish and same shape as far as possible, for accurate measurements.
The Reflectance Spectrophotometer has small view and large view sample mounting holders with small hole area or large area hole respectively to place sample to scan its surface for colour measuring and recording in the diode type detector to use for storing and analysis for comparison to obtain X,Y, Z or R or K/S values with
After that, the associated Computer aided colour match prediction software takes over the rest part of the work of calculations and comparison of colour data to show the measured values and calculated colour values using stored colour database of specific dyes for specific type of textile substrate. Table 1 shows Computer aided colour match prediction system (CACMPS) generated dyeing recipe and its dye cost and estimated approxmiation of Colour difference values with least metameric ratio for cotton fabric sample to be dyed to match against given standard samples using direct dye data base stored.
= | = | ||||||||||||||||
= | |||||||||||||||||
= | |||||||||||||||||
= | |||||||||||||||||
= | = | ||||||||||||||||
3 | |||||||||||||||||
5 | |||||||||||||||||
9 | |||||||||||||||||
4 | |||||||||||||||||
5 | |||||||||||||||||
9 | |||||||||||||||||
A case study of colour match prediction from the database of direct dye for cotton.
The above shown formulae of colour match prediction generated against standard shade C5, has generated two possible recipes, and is difficult to decide which one we should accept and proceed for bulk dyeing. From the Point of least metamerism, formulation-1 and from the point of least cost Formula −2 are respectively found better after 4 trial run in Computer aided colour match prediction system (CACMPS) within DE limit to 1.00. Thus, computer predicted formulation −2 is least cost and formulation −1 is least metameric in nature, as shown in output result generated here.
The practical aspects of data base generating match generation using a data base, setting up proper DE or multiple colour tolerance & above all accurate spectrophotometer measurement depends on following factors.
It is also essential to develop mutually agreeable pass/fail system between buyer or seller or by company itself for their shade control to match produced samples lot with the colour values of standard shade given, which should be specified by set up specific tolerance values of these colour difference criteria for any par of near matched textiles. These may be more important while considering batch to batch variation during production of shades as per match of standard samples given. As all textile dyers and dyeing units or composite textile mills have procured this computer aided colour match prediction system, this become a regular job to check match accuracy from shift to shift or lot to lot variation always, to understand the colour differences from standard shade given. So that the colour differences from batch to batch variation at factory /dye house in company production department, the shade may be corrected by revised addition of dyes, to obtain more precision match, so that chance of rejection in export level on this ground may be eliminated and for this, specific sets of colour tolerances values are decided and pre -set.
In practice in textile industry/ dye houses, for dyed /coloured cotton textiles, if not otherwise mentioned/specified, the thumb rule for setting a symmetric colour tolerances values in terms of dL*, da*, db* and dE* for effective colour matching of cotton textiles are as follows:
Standard set of colour tolerence values: dL* = 0.7 to 1.2; da* = 0.6 to 1.0 db* = 0.6 to 1.0; dE* = 1.0 to 1.5 applicable for selected common shades and common dyes for cotton. However, these colour tolerence limits for colour matching of dyed textiles could be somewhat narrower in case of requirement of precission matching. The main dependant factors responsible for lot to lot or batch to batch dyeing production with variation of shade are: i) weighing / solubilisation/dilution error, ii) substrate and pre treatment variation, iii) pretreatment or heat setting variation, and iv) Variation in dyeing conditions by change of dyeing process variables or variation in additive concentrations and 5) dye selected and its purity.
The calibration dyeing for preparation of dyestuff data base for dyeing specific textile fabrics with selected type and class of dyes is an essential pre requisite. After selection of substrate and class of dyes and dye manufacturer/suppliers), to run a computer aided colour measuring and matching system, preparation of dyestuff data base ton store using selective class and type of dyes, the control bleached cotton/ otherwise textile fabric sample are to be dyed with each selected dye at 5-8 different concentration levels of dyes (say, within 0.1 / 0.5 to 4%) and those samples dyed are to be subjected to measure their reflectance values at different wavelength and their individual values or their integrated sum of these REflectance / tristimulus colour values are to be stored for futurev uses to form a Dye class wise/company wise data bank or data base of all different type of dyes for specific substrate / substance following a particular standard process of dyeing in a separate file of the computerised processor or computer to use at every re-call. Samanta et al. [9, 10] mentioned the cares necessary for accuracy in colour measurement of textiles including nos. of folding etc. and orientation of samples and measure of colour difference index values etc. Randall and Stutts [11] specifies how to prepare reliable samples of calibration dyeing for creating dyestuff data base in computer aided colour matching system as a most important step. For optimum efficacy in computer aided colour matching system, the laboratory dyeing machine and process must be highly controlled in terms of dyeing process variables and all these must be standardised before callibration dyeing be carried out accurately, which is to be assured by the lab dyers /colourist to store precision colour data/ dyestuff database separately for company wise /substrate wise for separate class of dyes.
The accuracy of computer aided colour matching system depends on the correct dyestuff data base preparation as discussed in calibration dyeing in item 3.1 above. The accuracy of dyestuff data base can be checked by checking linearity of K/S vs. Dye Concentrations curve pattern for each individual dye applied on same substrate under standardised control dyeing conditions. Sometimes, this linear relation does not exist and then the deviation from linearity is to be eliminated, before such dyestuff data base are stored for future use of colour matching functions. The deviation from linearity of plot between K/S vs. dye concentration are due to (i) inherent variation in dye uptake rate or variation in exhaustion rate of the dye for higher percentage of dyes (ii) unknown interference of dyes with given dye bath auxialaries (iii) variation in dyeing conditions /stirring rate (iv) weighing/solubilisation/dilution error (v) impurities/agglomeration of few dyestuff itself, where these said reasons causes a variation of dyeing with increase in dye concentration [9] showing non linearity/deviation from linearity in observed. Dye uptake.
Therefore, this linearization is to be ultimately done by statistical best fit linearization process or elimination of one or two concentrations of dyes(where /from which point the said linearization is originated/deviated) for particular dye or by empirical modifications of the equation of K-M functions (K/S value). before storing dyestuff database to be used for colour match prediction of coloured textiles easily. For this type of special cases, the dye absorption co-efficient/difussion coefficient of the dye is to be determibned and to be checked at about five to eight level of dye concentrations to check the dyeing absorption/diffusion rate and then linearization can be made either eliminating few dye concentrations where dyeing rate is much varying. Repeat colouration is to be done to avoid variation in dyeing process variables to get correct data. Only after linearization of plots of K/S vs. Dye concentrations, the individual dyestuff data base may be stored in the computerised storing and saving file as ready made database for use in predicting recipe for colour matching formulations for specific substrate for specific dye class within user choiced/ standard tolerances of colour differences in terms of DE, DL, Da, Db values under standard illuminants of D65 or otherwise. If dyestuff cost are entered and uploaded and updated regularly, the dye cost of predicted colour matching formulations are also available along with predicted metamerism values.
Colour Matching of textiles is very much dependant on the Pigment /dye Database created –dye class based and type of fibre/fabric based and dye company based to be pre-up-loaded in spectro. To match full strength of colour, Light and dark i.e. white and black reduction are very important.
Pigments /dyes should be thoroughly dispersed and uniformly dyed, which is Very difficult with powder pigments, but much easier with Master batch mass pigmentation to produce coloured textiles.
There are so many variations in measuring surface colour of textiles. A measurement is never perfect. The effect of variability of colour measurement is reduced by using multiple measurements and taking avrages at 10 points atlesat. How many measurements should I make for averaging is a good question and Rule of thumb is 10 times atleast for each variability parameter of dyeing for standardising dyeing process variables. For any variable instrumental factors also, measure each spot of colour value for 10 times to take average of it. But for sample uniformity for data base storing data, one should repeat colour measurements at several locations — more than 10 to 100, depending CV % of K/S values or reflectance values of coloured textile surface. One can follow ASTM standard E 1345- 90 to determine how many measurements are necessary in each case.
Some more Practical Aspects of variability in colour mesurement of textile surface [9] are:
Level / Un level dyeing (Usually Less than 5% CV of K/S Value is taken as level dyeing for textiles).
Back ground opaqueness of the sample (No. of Folds are to be kept Constant say usually 4 fold).
Variation in warp wise or weft wise sample’s vertical/horizantal orientation may differ K/S value)
Variation in texture or surface roughness may vary K/S values for change in scattering (Any chemical/ physical intervention/Treatment before dyeing may change surface texture)
Variation of colour and texture in two sides of the fabric sample (K/S -surface colour strength in one face of fabric may sometimes differ from other face due to the said effect).
Any Fabric or Dyeing Defects/Stains in the fabric sample (Any defect of the fabric may cause colour variation).
Dull shade / Fluorescent colour & bright shade etc. some times behave differently.
Blended fabric may pose problem with change of Blend % of each component of fibres.
The reasons of variation of colours produced in textiles during data base preparations - are
Improper weighing and mixing of colourants.
Improper Cleanliness of dyeing machinery parts, like steam pipes and dye bath
In-compatable colour mixing and variation of dyeing time and other process variables
Interference from regrind/ slubilization of dyes having some chnaces of contamination.
Shedding of fibres / Degradation of fibres or chemicals used during processing.
Machine stoppages and inadequate steam purging in dye bath having in adequate temperature
Improper selection of Colourant/ Master-batch.
Interference with processing additives - chrome pigments containing lead will discolour if Tin stabilisers are present.
Moreover, different other cares are necessary, without which in-accurate measurement occur for measuring of colour values of textiles --e. g.
Accent on cleanliness: Poor housekeeping results colour contamination and stain,
Selecting correct Colourant and clear understanding of colour type and properties to specific textile fibre / polymer involved. Master-batch of colour supplier plays crucial role in this case.
Use of pre-coloured standard materials and best checking by replicating same colour on a same or different textiles. Cost of instrument is usually more
Inventory and logistics issues are there also for variation of colour and its measurement.
Use of Pigment colouring for small quantities where Master-batch development is easier.
Measurement of tristimulus values, reflectant at maximum absorbance wave length or K/S measurement of transmitants.
Calculation of colour difference by CIELAB equation of total colour difference i.e. ∆E* = [(∆L*) 2 + (∆a*) 2 + (∆b*) 2]½ with plot of CIE colour difference space diagram. The shade sorting i.e. pass/fail mechanism of quality control of dyed shades from batch to batch or lot to lot represents colour difference values in terms of Darkness and lightness (∆L*) Redness & Greenness (∆a and Yellowness and Blueness (∆b*).
Finger Tips solution of predicting newer computer aided d colour matching recipe /formulation with lowset cost & lowest metameric match recipe using pre- set stored speicific dyestuff data base.
Batch correction or auto correction of shades by manual or computerised corrections.
Extension of match Prediction by batch corrections and utilisation of dyeing waste liquor.
Purity/ Quality test of incoming newer batch of dyes with the help of this computer aided colour measuring system.
Determination of whiteness, yellowness and brightness indices of bleached textile substrate using different standard scales like CIE scale, Hunter Lab scale, ASTM-E-313 scale, Stansby scale etc.
Prediction of efficiency of OBA (optical brightening agents) utilising this system by change of with or without UV light setting.
More accurate and Quantitative understanding and grading of colour fastness grade for colour fading behaviour to wsah, crocking/rubbing. Exposure to UV light etc. replacing conventional grey scale rating.
Whiteness is assesment of freedom from any colour and contamination/stain /soil and as such it is taken as an indicator of quality for a bleached textile fabric prepared for dyeing. Objective measurement and meaningful numerical expression whiteness index as per CIE and Hunter lab scale are widely used. It represents whiteness index (WI) in terms of colorimetric values for the specimen and the chromaticity coordinates of the illuminant:
where x, y and Y are the colorimetric values for the sample under illuminant D65, and xn and yn are the chromaticity coordinates of the light source/illuminant used. A value for WI of 100 represents a perfect reflecting white diffuser, equivalent to surface of saturated paste of Magnesium sulphate.
X, Y and Z are the CIE tri-stimulus values of the sample and
Similrly, yellowness indices [12] as per ASTM-E313/1973 can be expressed as follows:
Where, X, Y and Z are the CIE tri-stimulus values of the sample,
Brightness Index (BI) as per ISO-2469/2470-1977method [13] can be calculated by following formula:
Treatment with fluorescent brightening agents can lead to reflectance values of up to 150. Although the pattern appears to become whiter, the change in appearance is due to a change in chroma towards blue, and this fact is expressed in quantitative form as the ‘tint factor’. Allied to the appearance of the uncoloured fabric is the yellowness, which suggests yellowing by chemical treatment or by heat scorching or degradation by light or by gases. Thus along with colour parameter the said other surface appearance properties are also very very important too in defining the quality of the surface appearance of any textiles.
Colour is one of the important element of a design. Colour with aesthetics /texture of anty textile fabrics / garments are as important as its physical and functional property criteria. Matching of colours, especially in specific textiles made from specific or different fibres and their blends is very very crucial in many applications. The task of communicating and measuring and matching of colour becomes more difficult when colours need to be exactly matched with a given standard supplied for different textiles. More and more precision colour matching is required in specialised textile products like defence dress materials, school uniform etc. and also for matching suits for consumer textiles and livestyle products for matched furnishings, bed linen and auto Interiors etc.
This Computer aided reflactance spectrophotometer is an impoartant tools/intrument for quality up grdation of textiles and garments by maesuring surface colour strength and colour dierences values as per CIE equations/ formulae. Some Other Application of computer aided colour measuring cum matching System used in textiles or apparel industry’s Dye House:
For quality control of dyed textiles including pass/fail decision of batch to batch checking.
For Evaluation of Quality of dyes supplied.
Effect of dyeing additives by measuring colour yield.
Efficiency of optical brighteners by UV analysis.
Soil removal efficiency of surfactants by measuring Reflectance value.
Measurement of whiteness / yellowness / brightness index etc. of undyed and bleached samples besides dyed samples.
Computer Aided Colour Measuring and Match Prediction System (CACMPS), now a days, become an essential tools for each textile dye houses to match colours or shade as per panton shade nos. or as per given samples, to reduce export rejection for colours. Moreover, to judge colour fastness grading more accurately from measurement of colour difference values after corresponding fading by wash or light or rubbing etc., than subjective/comparative judging by grey scale rating purpose is more scientific and advantegios. Quality control activity and batch to batch pass /fail checking of shades developed from shift to shift needs to be implemented in all dye houses for quality assurance on colour matching which is an integral demand of today’s apparel and fashion industry. Hence learning of colorimetric principles of UV VIS reflectance spectrophotometer and proper utilisation of this instrument carefully for deriving all round benefits out of it, for surface colour measuring and matching of textiles for customer satisfaction is also helps in brand building by quality assurance on colour matching of textiles.
The author is thankful to the Principal RBGC, Kolkata for her encouragement and support.
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Aalborg University has Two Satellite Campuses, one in Copenhagen (Aalborg University Copenhagen) and the other in Esbjerg (Aalborg University Esbjerg).\n· He is a member of prestigious IEEE (Institute of Electrical and Electronics Engineers), and IAENG (International Association of Engineers) organizations. \n· He is the chief Editor of the Journal of Software Engineering.\n· He is the member of the Editorial Board of International Journal of Computer Science and Software Technology (IJCSST) and International Journal of Computer Engineering and Information Technology. \n· He is also the Editor of Communication in Computer and Information Science CCIS-20 by Springer.\n· Reviewer For Many Conferences\nHe is the lead person in making collaboration agreements between Aalborg University and many universities of Pakistan, for which the MOU’s (Memorandum of Understanding) have been signed.\nProfessor Akbar is working in Academia since 1990, he started his career as a Lab demonstrator/TA at the University of Sussex. After finishing his P. hD degree in 1992, he served in the Industry as a Scientific Officer and continued his academic career as a visiting scholar for a number of educational institutions. In 1996 he joined National University of Science & Technology Pakistan (NUST) as an Associate Professor; NUST is one of the top few universities in Pakistan. In 1999 he joined an International Company Lineo Inc, Canada as Manager Compiler Group, where he headed the group for developing Compiler Tool Chain and Porting of Operating Systems for the BLACKfin processor. The processor development was a joint venture by Intel and Analog Devices. In 2002 Lineo Inc., was taken over by another company, so he joined Aalborg University Denmark as an Assistant Professor.\nProfessor Akbar has truly a multi-disciplined career and he continued his legacy and making progress in many areas of his interests both in teaching and research. He has contributed in stochastic estimation of control area especially, in the Multiple Target Tracking and Interactive Multiple Model (IMM) research, Ball & Beam Control Problem, Robotics, Levitation Control. He has contributed in developing Algorithms for Fingerprint Matching, Computer Vision and Face Recognition. He has been supervising Pattern Recognition, Formal Languages and Distributed Processing projects for several years. He has reviewed many books on Management, Computer Science. Currently, he is an active and permanent reviewer for many international conferences and symposia and the program committee member for many international conferences.\nIn teaching he has taught the core computer science subjects like, Digital Design, Real Time Embedded System Programming, Operating Systems, Software Engineering, Data Structures, Databases, Compiler Construction. 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In recent years, the application of chemistry to biological molecules has gained significant interest in medicinal and pharmacological studies. This topic will be devoted to understanding the interplay between biomolecules and chemical compounds, their structure and function, and their potential applications in related fields. Being a part of the biochemistry discipline, the ideas and concepts that have emerged from Chemical Biology have affected other related areas. This topic will closely deal with all emerging trends in this discipline.",annualVolume:11411,isOpenForSubmission:!0,coverUrl:"https://cdn.intechopen.com/series_topics/covers/15.jpg",editor:{id:"441442",title:"Dr.",name:"Şükrü",middleName:null,surname:"Beydemir",fullName:"Şükrü Beydemir",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0033Y00003GsUoIQAV/Profile_Picture_1634557147521",institutionString:null,institution:{name:"Anadolu University",institutionURL:null,country:{name:"Turkey"}}},editorTwo:{id:"13652",title:"Prof.",name:"Deniz",middleName:null,surname:"Ekinci",fullName:"Deniz Ekinci",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002aYLT1QAO/Profile_Picture_1634557223079",institutionString:null,institution:{name:"Ondokuz Mayıs University",institutionURL:null,country:{name:"Turkey"}}},editorThree:null,editorialBoard:[{id:"241413",title:"Dr.",name:"Azhar",middleName:null,surname:"Rasul",fullName:"Azhar Rasul",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRT1oQAG/Profile_Picture_1635251978933",institutionString:null,institution:{name:"Government College University, Faisalabad",institutionURL:null,country:{name:"Pakistan"}}},{id:"178316",title:"Ph.D.",name:"Sergey",middleName:null,surname:"Sedykh",fullName:"Sergey Sedykh",profilePictureURL:"https://mts.intechopen.com/storage/users/178316/images/system/178316.jfif",institutionString:null,institution:{name:"Novosibirsk State University",institutionURL:null,country:{name:"Russia"}}}]},{id:"17",title:"Metabolism",keywords:"Biomolecules Metabolism, Energy Metabolism, Metabolic Pathways, Key Metabolic Enzymes, Metabolic Adaptation",scope:"Metabolism is frequently defined in biochemistry textbooks as the overall process that allows living systems to acquire and use the free energy they need for their vital functions or the chemical processes that occur within a living organism to maintain life. Behind these definitions are hidden all the aspects of normal and pathological functioning of all processes that the topic ‘Metabolism’ will cover within the Biochemistry Series. Thus all studies on metabolism will be considered for publication.",annualVolume:11413,isOpenForSubmission:!0,coverUrl:"https://cdn.intechopen.com/series_topics/covers/17.jpg",editor:{id:"138626",title:"Dr.",name:"Yannis",middleName:null,surname:"Karamanos",fullName:"Yannis Karamanos",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002g6Jv2QAE/Profile_Picture_1629356660984",institutionString:null,institution:{name:"Artois University",institutionURL:null,country:{name:"France"}}},editorTwo:null,editorThree:null,editorialBoard:[{id:"243049",title:"Dr.",name:"Anca",middleName:null,surname:"Pantea Stoian",fullName:"Anca Pantea Stoian",profilePictureURL:"https://mts.intechopen.com/storage/users/243049/images/system/243049.jpg",institutionString:null,institution:{name:"Carol Davila University of Medicine and Pharmacy",institutionURL:null,country:{name:"Romania"}}},{id:"203824",title:"Dr.",name:"Attilio",middleName:null,surname:"Rigotti",fullName:"Attilio Rigotti",profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",institutionString:null,institution:{name:"Pontifical Catholic University of Chile",institutionURL:null,country:{name:"Chile"}}},{id:"300470",title:"Dr.",name:"Yanfei (Jacob)",middleName:null,surname:"Qi",fullName:"Yanfei (Jacob) Qi",profilePictureURL:"https://mts.intechopen.com/storage/users/300470/images/system/300470.jpg",institutionString:null,institution:{name:"Centenary Institute of Cancer Medicine and Cell Biology",institutionURL:null,country:{name:"Australia"}}}]},{id:"18",title:"Proteomics",keywords:"Mono- and Two-Dimensional Gel Electrophoresis (1-and 2-DE), Liquid Chromatography (LC), Mass Spectrometry/Tandem Mass Spectrometry (MS; MS/MS), Proteins",scope:"With the recognition that the human genome cannot provide answers to the etiology of a disorder, changes in the proteins expressed by a genome became a focus in research. Thus proteomics, an area of research that detects all protein forms expressed in an organism, including splice isoforms and post-translational modifications, is more suitable than genomics for a comprehensive understanding of the biochemical processes that govern life. The most common proteomics applications are currently in the clinical field for the identification, in a variety of biological matrices, of biomarkers for diagnosis and therapeutic intervention of disorders. From the comparison of proteomic profiles of control and disease or different physiological states, which may emerge, changes in protein expression can provide new insights into the roles played by some proteins in human pathologies. Understanding how proteins function and interact with each other is another goal of proteomics that makes this approach even more intriguing. Specialized technology and expertise are required to assess the proteome of any biological sample. Currently, proteomics relies mainly on mass spectrometry (MS) combined with electrophoretic (1 or 2-DE-MS) and/or chromatographic techniques (LC-MS/MS). MS is an excellent tool that has gained popularity in proteomics because of its ability to gather a complex body of information such as cataloging protein expression, identifying protein modification sites, and defining protein interactions. The Proteomics topic aims to attract contributions on all aspects of MS-based proteomics that, by pushing the boundaries of MS capabilities, may address biological problems that have not been resolved yet.",annualVolume:11414,isOpenForSubmission:!0,coverUrl:"https://cdn.intechopen.com/series_topics/covers/18.jpg",editor:{id:"200689",title:"Prof.",name:"Paolo",middleName:null,surname:"Iadarola",fullName:"Paolo Iadarola",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bSCl8QAG/Profile_Picture_1623568118342",institutionString:null,institution:{name:"University of Pavia",institutionURL:null,country:{name:"Italy"}}},editorTwo:{id:"201414",title:"Dr.",name:"Simona",middleName:null,surname:"Viglio",fullName:"Simona Viglio",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRKDHQA4/Profile_Picture_1630402531487",institutionString:null,institution:{name:"University of Pavia",institutionURL:null,country:{name:"Italy"}}},editorThree:null,editorialBoard:[{id:"72288",title:"Dr.",name:"Arli Aditya",middleName:null,surname:"Parikesit",fullName:"Arli Aditya Parikesit",profilePictureURL:"https://mts.intechopen.com/storage/users/72288/images/system/72288.jpg",institutionString:null,institution:{name:"Indonesia International Institute for Life Sciences",institutionURL:null,country:{name:"Indonesia"}}},{id:"40928",title:"Dr.",name:"Cesar",middleName:null,surname:"Lopez-Camarillo",fullName:"Cesar Lopez-Camarillo",profilePictureURL:"https://mts.intechopen.com/storage/users/40928/images/3884_n.png",institutionString:null,institution:{name:"Universidad Autónoma de la Ciudad de México",institutionURL:null,country:{name:"Mexico"}}},{id:"81926",title:"Dr.",name:"Shymaa",middleName:null,surname:"Enany",fullName:"Shymaa Enany",profilePictureURL:"https://mts.intechopen.com/storage/users/81926/images/system/81926.png",institutionString:"Suez Canal University",institution:{name:"Suez Canal University",institutionURL:null,country:{name:"Egypt"}}}]}]}},libraryRecommendation:{success:null,errors:{},institutions:[]},route:{name:"chapter.detail",path:"/chapters/36738",hash:"",query:{},params:{id:"36738"},fullPath:"/chapters/36738",meta:{},from:{name:null,path:"/",hash:"",query:{},params:{},fullPath:"/",meta:{}}}},function(){var e;(e=document.currentScript||document.scripts[document.scripts.length-1]).parentNode.removeChild(e)}()