electronic colour communication in the textile and ... - senai cetiqt

www.cetiqt.senai.br/redige │ 43 │

Electronic colour communication in the textile and apparel

industry

Dr. Robert Hirschler Technical Advisor, Colour Institute, SENAI/CETIQT, Brazil

Abstract

Colour communication is of utmost importance in the textile and apparel industry, and

communicating numbers which describe colours unambiguously has been possible since the

international acceptance of the CIE system of colour measurement. Although today universally

used, instrumental colour measurement has its limitations. Advances in the calibration and colour

management of input, display and output devices have made it possible to communicate not only

numbers, but also high colour fidelity images. Non-contact colour measurement based on

controlled standard illumination and a calibrated camera opens new possibilities in the colour

specification of small, curved and patterned samples which could not be measured with

conventional instruments.

Keywords: Colour communication. Colour management. Colorimetry.

1 Introduction

The first attribute attracting a customer to select a piece of fabric or garment is its

colour. A pleasing colour or colour combination is one of the strongest sales weapons, but

the way the colour may be communicated from mind to market (i.e. from the designer to

the final customer) is a very complex one. There are different levels of colour

communication from the simple verbal through colour collections, colour order systems to

instrumental and virtual, each with their respective advantages and disadvantages

(HIRSCHLER, 2011).

Verbal colour communication can be very simple, using words like red, green, blue;

somewhat more detailed like dark red, grass green, sky blue, or very systematic, like

“light yellowish brown” (KELLY; JUDD, 1976), but it will always lack the precision needed

in industry. Using a colour sample collection (like Pantone) or a colour order system

(such as the Munsell system) helps, and the Munsell system even permits visual

interpolation between the samples in the colour collection, thus making it a useful tool in

non-instrumental colour communication. The most important characteristic of the Munsell

system is that it describes colour in perceptual terms Hue (what we generally call the

name of the colour: blue, green, yellow, orange, red etc.); Value (or lightness, i.e. lighter

– darker) and Chroma (which is similar to the saturation or the purity of the colour). The

colours are arranged in three dimensions as illustrated in Figure 1.

R. Hirschler REDIGE v. 1, n. 1, 2010

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Figure 1 – The MUNSELL colour order system as illustrated by the Munsell Color Tree Credits: Color Tree produced by Munsell Color Services® of X-Rite Inc. (www.munsell.com)

Instrumental colour communication had its beginning when the first industrial

spectrophotometer (the “Hardy”) became available in 1929, and two years later the CIE

(Comission Internationale de lÉclairage – International Commission on Illumination)

system of colorimetry was born. This made way of putting numbers on colours, but it

took over 30 years more for the first real electronic exchange of colour data to take place

in an industrial scale. In 1963 ICI announced a new service for the textile industry, called

IMP – Instrumental Match Prediction (ALDERSON et al., 1963), which today would be

called Computerized Colorant Formulation. The mere fact of calculating recipes by

computers wasn’t exactly new; the Davidson and Hemmendinger COMIC analogue

computer had been doing it since 1958, but there was a brand new concept in the

communication of colour data. The customer would measure the tristimulus values of the

required colour (the target) on a colorimeter, send them by telex (anybody still

remembers?) to the ICI Dyestuffs Division Headquarters in Blackley, and would receive

within a few hours the recipe for that particular colour. Figure 2. shows the computer

installation with the then extremely potent Elliott 803B computer (boasting 8 kilobytes of

computing capacity) in the back of the room, while to the left of the picture we can see

the communicating devices – the telex machines.

http://www.munsell.com/�


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Figure 2 – General view of the computer installation for the IMP system in Blackley Credits: ICI publication (1963) with kind permission of DyStar Colours Deutschland GmbH

By today’s standards we may smile at the level of the computer and communications

technology available in the early 1960’s, but it was all there for electronic colour

communication: specifying colours in numerical terms and sending digital data across

countries or continents.

2 Instrumental Colour Specification

For colours to be objectively communicated we need to put numbers on them, and there

are different sets of numbers with which colours may be specified.

Object colours can be measured by spectrophotometers, which will provide spectral

reflectance or spectral transmittance values. From the spectral reflectance values basic

colorimetric quantities, the X, Y, Z tristimulus values, may be computed in the CIE

system of colour measurement (SCHANDA, 2007) and these may be transformed into

CIE L*, a* and b* (CIELAB) coordinates which are related to the way we characterize

colours in visual (perceptual) terms. Tristimulus values (and, consequently, CIELAB

coordinates) may also be computed directly from the RGB values of digital input devices

such as digital cameras, scanners, or the RGB settings of monitors.

2.1 Spectral Reflectance Values

For object colours the spectral reflectance values may be considered their “digital

fingerprints” – they tell us which part of the visible spectrum is absorbed and which part

is reflected by the object. They are best understood by plotting reflectance as a function

of wavelength to get the spectral reflectance curves. On these diagrams the horizontal

axis shows the wavelength (i.e. the arrangement of the spectrum from violet and blue

through green, yellow and orange to red), and the vertical axis the relative amount of


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light reflected. Although they are difficult to be accurately interpreted in visual term there

is a certain relationship between the shape of the curve and basic visual characteristics.

Figures 3. to 5. illustrate the spectral reflectance curves of some selected samples from

the MUNSELL colour collection, one of the best known and most widely used colour order

systems.

Figure 3 – Spectral reflectance curves of selected MUNSELL samples of the same Value

and Chroma, differing only in Hue.

Differences in hue, as can be seen in Figure 3., are caused by the differences in the

shape of the curve. A red colour would have low reflectance in the blue and green region

of the spectrum and high reflectance in the red region. A yellow object would reflect both

green and red, and absorb mainly in the blue region. A pure green is characterized by

low reflectance in the blue and red regions, and high reflectance in the green region.

Figure 4 - Spectral reflectance curves of selected MUNSELL samples of the same Hue and

Chroma, differing only in Value (lightness).

Colours of the same Hue and Chroma have very similar curve shapes (Figure 4.), the

characteristic difference due to the differences in Value (lightness) are those of the


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height of the curve: the lighter the colour (higher Value) the higher the reflectance.

Figure 5 - Spectral reflectance curves of selected MUNSELL samples of the same Hue and

Value, differing only in Chroma.

Higher Chroma colours have steeper curves, the neutral grey (N6) is practically flat, the

highest chroma colour has the steepest curve (Figure 5).

It must be emphasized that these rules are very general. Spectral values in themselves

are not sufficient to communicate the visual appearance of colours, for this we have to

take into consideration the effect of illumination and the way a human observer sees

colours.

2.2 CIE Tristimulus Values and Metamerism

Colour is three-dimensional, we can describe any colour with three attributes such as the

MUNSELL coordinates Hue, Value and Chroma, or the ones used in the NCS system: hue,

white content and black content. The CIE system of colour measurement reduces spectral

data of objects into three numbers called tristimulus values in such a way that the

characteristics of the illumination and the way a human observer perceives colours are

also taken into consideration.

One set of X, Y and Z tristimulus values describes the colour of an object for one

particular CIE illuminant and one of the two CIE standard observers. In the calculation of

the tristimulus values we reduce the 16, 32 or more spectral reflectance values to three

numbers, thus we are necessarily losing some of the information. Whereas for any one

illuminant/observer condition there is only one corresponding set of tristimulus values,

the reverse is not true: there can be an infinite number of spectral curves (sets of 16, 32

or more spectral reflectance values) which yield the same X, Y and Z set (for that

particular illuminant/observer condition). These curves are said to define metameric

colours, which have identical tristimulus values (and therefore look exactly the same)

under a particular illuminant for a given observer, but have different tristimulus values


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(and therefore do not look the same) if either the illuminant or the observer (or both) are

changed, as illustrated in Table 1. and in Figure 6.

Table 1: Tristimulus values of two metameric grey specimens

Illuminant D65 / 10 degree observer

X1 = X2 = 27.0 Y1 = Y2 = 28.5

Z1 = Z2 =

30.4

Illuminant A / 2 degree observer

X1 = 31.1 Y1 = 28.5 Z1 = 10.1

X2 = 32.5 Y2 = 28.5 Z2 = 10.4

Figure 6 - Spectral reflectance curves of two metameric grey specimens, with tristimulus values as shown in Table 1.

The example shows the different reflectance curves of two grey specimens (Figure 6.)

with tristimulus values calculated for two illuminant/observer conditions (Table 1.) In

spite of the reflectance curves showing significant differences, the two colour appear

identical under illuminant D65 (standard daylight) for the 10 degree observer. If either

the illuminant or the observer changes, the two specimens will show a colour difference,

for example the one shown in Table 1. for illuminant A (tungsten light) and the 2 degree


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observer.

When communicating colours through tristimulus values (such as was the case of the IMP

system described in the Introduction) it must always be made very clear to which

illuminant and observer condition these values have been computed.

Although in the definition of the tristimulus values the way an average human observer

sees colours is incorporated, they do not describe colours in perceptual terms. We can

vaguely say that the X tristimulus value represents the red, the Y the green and the Z

the blue stimulus, but the most we can say with certainty is that when two sets of

tristimulus values are identical the colours appear to be the same, but if they are

different we cannot say (just by the tristimulus values) exactly how different the colours

are. For communicating these differences (and establishing tolerances) we need to

transform the X, Y and Z values into a colour space which describes perceptual properties

and differences better, notably into CIELAB coordinates.

2.3 CIELAB Coordinates, Colour Differences and Tolerances

The great advantage of the CIE 1976 L*a*b* (abbreviated CIELAB) object-colour space is

the similarity of the arrangement of colours to that of the Munsell space (see Figure 1.)

In CIELAB space the L* vertical axis represents lightness (from black in the bottom and

white on top); the a* axis is the direction of redness, -a* is greenness, b* yellowness

and –b* blueness. Colours of different hues (but constant lightness and chroma) are

arranged in concentric circles around the neutral (grey) colours in the middle.

CIELAB coordinates are calculated from the X, Y and Z tristimulus values, and thus the

same restrictions apply to them: they are always representing one illuminant / observer

condition; from the same set of spectral reflectance values we get different sets of L*, a*

and b* coordinates if we change either the illuminant or the observer (or both). For

metameric colours it is also true (as for the XYZ values) that CIELAB coordinates are the

same in spite of different spectral reflectance values (for one illuminant / observer

condition).

In recent years communicating colours through CIELAB values has gained special

importance in the digital world, as we shall see later (in Section 3.1), because they are

device independent (as opposed to device dependent RGB or CMYK values). In the textile

and apparel industry CIELAB values themselves are rarely used, their special importance

lies in their application for the evaluation and communication of colour differences.

We have already mentioned that tristimulus values (and their differences) are not good

descriptors of colour differences; CIELAB is preferred for this application. In CIELAB

space we can calculate the distance between the points representing different colour

stimuli, this distance is called the colour difference, usually designated as *abE∆ . We

should mention here that there are other colour coordinate systems still in use (albeit

obsolete) having L, a, b coordinates (Hunter, Adams-Nickerson) and DE as colour

difference; and the use of the asterisk is important to designate CIELAB not only for


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*abE∆ but also for the individual L*, a* and b* coordinates. The total colour difference

*abE∆ may be split into its components of *L∆ (lighter-darker) and either *a∆ (redder-

greener) and *b∆ (yellower-bluer) or *abC∆ (chroma difference) and *

abH∆ (hue

difference). (The ab index is important to distinguish these quantities from their

analogues in the CIE L*u*v* system).

Communicating colour differences is of primary importance in the textile and apparel

industry, because that is how we may decide if a product conforms to the colour

specifications within tolerance. Very soon after the introduction of the CIELAB system it

was confirmed that although it is a very useful tool it is not very efficient in making single

number pass/fail decisions (colour tolerancing). In the textile industry one of the most

difficult questions is “is this colour difference commercially acceptable or not”. Ideally we

could say: “if the measured colour difference is less than 1 *abE∆ unit, it is acceptable, is

it’s more, then not”. Unfortunately, we are very far from this ideal situation, for two

reasons.

The first reason is that CIELAB (good as it is) is not entirely uniform across colour space,

and for the same article and the same client the size of the acceptable colour difference

varies not only from colour to colour (i.e. it is different for reds and blues, light and dark

colours etc.) but depends also on the direction of the difference (i.e. it may be larger if

the difference is in lightness, but smaller if it is in hue). One solution for this problem is

to set up individual tolerances for every colour (generally around selected colour points),

but in industry it is well-nigh impossible. The best solution, however, is to calculate from

the CIELAB coordinates colour differences according to one of the colour tolerance

equations (CMC or CIEDE2000) which “distort” colour space in such a way as to conform

better to the visual judgement of trained professionals.

The other reason why we cannot give only one number as THE acceptable colour

difference (be it CIELAB, CMC or CIEDE2000) is that the decision whether a given colour

difference is acceptable or not is as much of a commercial as a technical question. The

size of the acceptable colour difference (the tolerance limit) depends on the product and

on the end-users demands. Generally the tolerance limits for fabrics sent to retail are

more generous than for the same fabric sent to a large garment manufacturer. The

tolerance for a fashion article may be more lenient than for uniforms. Also, customers

willing to pay more may demand stricter tolerances.

In the SENAI/CETIQT Colour Institute we have, over the years, performed over 50,000

pass/fail evaluations in nearly a dozen textile companies, and compared the judgement

of a group of trained colourists to the instrumental evaluation utilizing different colour

tolerance formulae (GAY; HIRSCHLER, 2002; GAY; HIRSCHLER, 2003).

We have found that for one company the tolerance limit had to be set as tight as DECMC =

0.7 and for another it could be as high as DECMC = 2.3 to agree with the judgement of the

visual panel of 8 to 12 observers (considered to be the “right” decision). If tolerance


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limits were established individually for each major product group and either the CMC or

the CIEDE2000 formula was used the percentage of right instrumental decisions was

around 80%. This is somewhat better than the percentage of right individual visual

decisions.

We may conclude that colour differences (or rather, tolerances) may be communicated

with high precision, provided that an adequate colour difference formula is used and the

necessary preliminary work of establishing acceptability limits for the given product

group has been correctly done.

2.4 Communication between Colour Measuring Instruments

Many people take it for granted that once a colour is measured (i.e. we can express it in

numbers, be they spectral reflectance, X, Y, Z tristimulus or CIELAB values, or some kind

of colour difference) we may freely communicate it, and the result will be perfect

understanding of exactly which colour we mean. Unfortunately, this is not so. There are

always some differences between measurements made on different instruments, even if

we make sure that they are in perfect operating conditions. The performance of colour

measuring instruments may be specified following the ASTM Standard Practice for

Specifying and Verifying the Performance of Color-Measuring Instruments (2008). In the

Colorimetry Laboratory of the SENAI/CETIQT Colour Institute different sets of Ceramic

Colour Standard tiles (CCS) are used for verifying instrument performance. The master

sets have been calibrated by the National Physical Laboratory (NPL) in Teddington, UK.

Repeatability shows how well the readings of an instrument are repeated over a short or

medium term. In modern industrial instruments in good conditions repeatability is

excellent; it is in the order of a few hundreds of *abE∆ units, more than one order of

magnitude below the perceptibility level.

Reproducibility may refer to inter-instrument agreement (a form of reproducibility in

which two or more instruments from the same manufacturer and model are compared)

or to inter-model agreement, a form of reproducibility in which the measurements of two

or more instruments from different manufacturers are compared. Needless to say in the

latter case the comparison only makes sense if the instruments (albeit of different

models) have the same measurement geometry. From the point of view of colour

communication reproducibility is extremely important, because we are generally

comparing measurement results from different locations, if possible between instruments

of the same model, but this is not always the case. Inter-instrument agreement for top-

of-the-line instruments may be as good as 0.15 to 0.3 *abE∆ units (average obtained on

the CCS set), i.e. just below or around the visual perceptibility limit. Inter-model

agreement may be much worse, around 0.5 *abE∆ units or more, which may be

considered above the perceptibility limit, and in the order of what is often considered the

industrial acceptability limit.


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It makes very little sense to communicate colours with such large uncertainty, and the

manufacturers have tried different methods to improve repeatability. In the 1990’s

Datacolor International launched what was called their “close tolerance” (CT) models of

the SF 500 spectrophotometer. Our laboratory exchanged data with two other

laboratories in the United States, and for the set of CCS we got inter-instrument

agreement of around 0.15 *abE∆ units, perfectly acceptable for colour communication. In

order to make advantage of this type of arrangement the users had to purchase the

same model of instruments, preferably within a reasonably short time period.

Datacolor has since improved and extended the method which is now incorporated in the

company’s Maestro package (utilizing a set of CCS tiles provided by Datacolor). A similar

method, the NetProfiler, was launched in the late 1990’s by GretagMacbeth (now X-Rite)

which makes use of the potential offered by communicating through the Internet.

Vasconcellos (2001) compared the performance of a Datacolor SF600 with a

GretagMacbeth CE7000 and found that the inter-instrument agreement was reduced

(improved) from 0.36 *abE∆ to 0.094 *

abE∆ through profiling with the NetProfiler. Datacolor

(2010a) published a study on the Internet comparing the two methods, and arrived at

the following highly interesting conclusions:

• Both profiling programs were able to improve the inter-instrument agreement on

BCRA tiles, but with consistency only for their own instruments;

• Improvements in BCRA agreement did not produce similar improvements in textile

agreement;

• The instrument diagnostic routines of the two profiling programs did not identify

problems with the non-native instruments.

Their final conclusion was that

These tests confirm that improvements in inter-instrument agreement gained

through profiling of a properly functioning spectrophotometer are insignificant

when compared to the error introduced by poor measurement technique, changes

due to sample conditioning, and operator error.

3 Virtual Colour Communication

Communicating colours by numbers is all very well, but what would really be nice is to

show you on your end of the line what I see here on my end – which is what virtual

colour communication is all about. Nowadays this appears to be very simple: I have a

digital camera or a scanner, enter the colour (or a complex design of many colours) into

some software, send the file to you over the Internet, and you just see it on your monitor

or print it out on your printer. Right? Wrong! As we shall see, there is more to it than

meets the eye (literally). If you ever tried to compare the image you have on the monitor

to the original you have just scanned in, or compare the print from your printer to the


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monitor image, or the original you were very likely most disappointed – unless you are

using colour management.

3.1 Device dependent colour

In today’s world of digital imaging we can’t really get even acceptable colour

reproduction across the media without colour management, and yet, it is a technique not

at all well known, and even less well understood. Why do we need colour management?

To understand this rather complex problem we have to first think about the different

ways colours are produced (Figure 7.)

0

10

20

30

40

50

400 450 500 550 600 650 700

Ref

lect

ance

(%)

Wavelength (nm) Figure 7 - Object colours (left); additive mixing (middle) and subtractive mixing (right)

Object colours are produced by the selective absorption and reflexion across the visible

spectrum depending on the combination of colorants used, and this is the “original” what

we scan in or take a photo of. Monitors, scanners and digital camera work in a different

way. They mix colours from three additive primaries red, green and blue (hence RGB),

which works because human colour perception is also based on RGB primaries, thus

additive mixing obeys the laws of psychophysics. Office printers produces colours by

subtractive mixing (obeying the laws of physics) based on three subtractive primaries

yellow, magenta and cyan (hence YMC). For technical reasons the great majority of these

printers uses a fourth colour, black (K), and therefore we usually speak of the YMCK

system. Here we are back again to an object colour, prints can be characterized by their

spectral reflectance curves, but these will inevitably be very different from those of the

originals. Even if we got a perfect match between original and print (for one illuminant /

observer condition) these colours would be highly metameric. (We may remark here that

some of the most recent digital textile printers work with 6 or 8 inks, and there the

resulting colour will be the combination of these, and thus metamerism may be reduced.)

Let’s see a real world example of how colours are produced on two monitors (from the

same scanned RGB values) and on two printers (from the same Photoshop file) as

compared to the original.


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0

10

20

30

40

50

400 450 500 550 600 650 700

Ref

lect

ance

(%)

Wavelength (nm)

OriginalLaserWax

0

10

20

30

40

50

60

400 450 500 550 600 650 700

Rad

ianc

e (W

/sr c

m²n

m)

Wavelength (nm)

LCD

CRT

Figure 8 – Spectral reflectance curves of a grey original and two prints (left) and the same grey as it appears on a CRT and an LCD monitor (right).

We can see on the left of Figure 8. that although the original neutral grey is reasonably

well reproduced by the laser printer, there is a high degree of metamerism between the

two. The wax printer printed the same grey much lighter, and the colour is also highly

metameric both to the original and the laser print. On the right we see how the two

monitors produce the same colour: here we can detect significant colour difference, and

even if the colours were adjusted to appear the same there would be a high degree of

metamerism.

As if these basic differences between the way colours are formed were not enough, there

can be (and generally there are) great differences even between similar devices. A

monitor can “understand” instructions given in RGB values. When we scan in the same

colour on different scanners, they will provide three more or less different sets of RGB

values – how can we then expect the monitor to show the same colours? And if we have

another monitor, which will interpret the same RGB value set in a different way, so we’ll

end up with different colours on the two monitors even if we enter the same RGB values,

as illustrated in Figure 9.

Figure 9 – Uncalibrated input and output devices result in unmanaged colours. Colours are for illustration purposes only; the colour differences shown are vastly exaggerated

Similarly, even when we give the same CMYK instructions to different printers the output

will be different (just as it happened in our example of the laser and the wax printers).


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We say that RGB and CMYK instructions are device dependent, and to deal with them we

have to apply colour management.

3.2 Colour Management

According to Wikipedia (2010) “In digital imaging systems, colour management is the

controlled conversion between the colour representations of various devices, such as

image scanners, digital cameras, monitors, TV screens, film printers, computer printers,

offset presses, and corresponding media.”

In a simple case we have one input device (scanner or digital camera), a display device

(monitor) and an output device (printer). By carefully studying the characteristics of each

device each can be “calibrated” against the other, and thus the monitor and the printer

shall show the same colours as present in the scanned original as illustrated in Figure 10.

Figure 10 – Closed-loop colour-managed system where each device is individually

calibrated against each other device

This is a lot of work; each new device that we wish to use in the system has to be

individually calibrated against all the others. This closed loop colour control becomes

unmanageable if there are more input, display and output devices. The solution is to

create one central “switchboard” called the profile connection space, which is

implemented in the open-loop systems.

In the open-loop system there is no “calibration” between devices, a general purpose

profile is created for each device, which communicates the device characteristics to the

connection space, and receives the information from other devices also in this

standardized form. For this to work we need to convert (through profiling) the device-

dependent RGB or CMYK values into device-independent CIELAB colour space.

To explain how a profile works we may take the example of three scanners, which

produce three sets of (device dependent) RGB values for the same red colour. Device

profiling finds the equivalent CIELAB values for each, and the whole point of colour

management is that from three different sets of RGB values (which represent the very

same colour) we should arrive at one set of (device independent) CIELAB values as

illustrated in Figure 11. By the same token if we send the (device independent) CIELAB


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values to different output devices (monitors, printers), they would each convert it back

into their (device dependent) RGB resp. CMYK values, and thus produce the same colour

as was scanned in from the original.

Figure 11 – Device dependent RGB values are converted into device independent CIELAB

values through the device profiles. 3.3 Virtual Colour Communication in the Textile and Apparel Industry

In the previous section we have seen how digital colour communication works beyond

traditional, spectrophotometry-based colorimetry. New technologies in image capture and

processing together with the technology of colour management have made it possible to

communicate not only the colour of relatively large uniform spots (which may be

measured on a conventional instrument) but also that of complex images.

Virtual colour communication can also be helpful where traditional colorimeters or

spectrophotometers have their limitations. Conventional instruments cannot measure

very small specimens (such as pieces of yarn), multicoloured or non-uniform surfaces

such as highly structured lace and multicoloured pile fabric. In order to overcome these

limitations digital imaging systems (cameras or scanners) may be used which capture the

total colour and appearance of 2D and 3D objects including those with irregular, curved

or non-uniform surfaces. Colours are characterised by the image formed on a monitor

and/or by the colorimetric values RGB. In this case the quality of the illumination

(irrelevant in spectral measurements) is of utmost importance, and in order to ensure

the repeatability and reproducibility of the measurements well defined and well controlled

illumination is necessary.

In the early days imprecise on-screen colour was considered the weakest link in the

application of virtual colour in the production chain. In the textile and apparel industry

the first attempts to improve the precision of on-screen colour for image communication

go back to the 1980’s when the first CAD systems were started to be used. Researchers

at UMIST (HAWKYARD; OULTON, 1991) and also of the LUTCHI Research Centre at the

University of Loughborough (LUO et al., 1992) developed closed loop control systems for

textile and apparel applications. The UMIST research resulted in the ShadeMaster system

first marketed by a textile CAD company called Textile Computer Systems (TCS) Ltd. The

ShadeMaster simulated object colours as shown under standard D65 illuminant (Figure

12.) and, in addition to monitor and printer calibration, it specified colours according to


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CIE X, Y and Z tristimulus values, CIELAB coordinates and also generated synthetic

reflectance curves.

Figure 12 – Coloured objects shown under simulated D65 standard illuminant in the TCS

ShadeMaster system Credits: Photos by the author, 1991

In 1996 UMIST developers founded Colorite (U.K.) Ltd., and sold the product as

ImageMaster. In 1997, Datacolor acquired Colorite, and ImageMaster became

ENVISIONTM, which is still part of the Datacolor suite of colour communication software

with image separation; colour creation and selection; spectrophotometer input; colour

visualization under various lighting conditions; monitor calibration, printer calibration;

colour library with search and retrieve functions (DATACOLOR 2010b).

ChromaShare (2010) have extended the concept of colour management well beyond the

definition given above in Section 3.2. Their modular SmartClient Colour Management

Software covers all the most important functions a user may need for visual colour

communication:

• CS PaletteShare - measure, save, search and edit palettes and libraries of colours;

• CS ImageShare - add full image separation and analysis features;

• CS WorkFlow - initiate and manage colour requests from your supply chain.

Figure 13. shows how images, parts of images, palettes and colour data may be

communicated between supplier and client.


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Figure 13 – Screen shot from the ChromaShare ImageShare module

Credits: Courtesy of Andrew Bennett, ChromaShare

As the software works over the Internet users can share the same colour experience

from anywhere in the world, enabling enterprise-wide colour management and decision

making. Images, graphics, and production data, can not only be readily exchanged, but

visualised too. The user’s web site can be enabled so that his customers can see the

palettes and images and graphics that he wants to be shared. Global colour management

means that different RGB versions of palettes, artwork and photos are sent to each user,

depending on their monitor - but they all share the same, calibrated visual result!

One of the most complex issues of colour communication in the textile and apparel

industry is that of working with images of structured textile substrates, where the

structure fundamentally influences the apparent colour. Traditional colour measurement

cannot cope with this situation, and until recently transmitting complex images in true

colour proved to be extremely problematic. LUTCHI researchers (LUO et al., 1992)

developed a commercial product called ColourTalk in which computer-based colour

models have been implemented, integrated with a viewing cabinet for visual colour

matching tasks and a networked spectrophotometer for colour measurement. The

research was later transferred to the University of Derby’s Colour & Imaging Institute

(RHODES; LUO, 1996) where the concept of a new product, the DigiEye was developed

(LUO, 2006).


_______________________________________________________________________________


Figure 14 – The DigiEye system for high-precision virtual colour communication

Credits: Photo courtesy of VeriVide Ltd.

Figure 15 – The DigiEye Large Area Imaging Cabinet can communicate the image and the

colour of entire pieces of garment Credits: Photo courtesy of VeriVide Ltd.

The DigiEye system is based on controlled illumination (simulating the CIE D65 standard

illuminant), a digital camera and a monitor colour managed to provide images with a

high degree of colour fidelity (Figure 14.) The simulated D65 illumination may also be

provided in a large area format making it possible to communicate images (and colours)

of pieces too large for the standard DigiEye box (Figure 15.)


_______________________________________________________________________________


Virtual colour communication with such a system may consist of transmitting the

“calibrated” image, where the colours at the receiving end (calibrated monitor or printer)

are very nearly identical to the originals. Showing the full image has the advantage that

in the case of patterned images (such as prints, jacquards etc.) not only the individual

colours but also the interactions among them are communicated. The DigiEye system

also has a module called DigiPix for the non-contact measurement of those specimens

which are too small, patterned, curved or otherwise unsuitable to be measured on

conventional instruments. In this case the measurement is based on RGB values

provided by the calibrated digital camera, under standard illumination and converted by a

special algorithm into synthetic reflectance curves which may be used for full colour

communication e.g. fed into a recipe prediction system.

4 Conclusion

Electronic colour communication has come a long way since the introduction of

instrumental colour measurement. It started with the simple transfer of colorimetric data

over whatever means of communication was available in those days and has evolved into

the instantaneous transmission of images and the possibility to visualize them with high

colour fidelity on a monitor or printer. Electronic colour communication facilitates

information processing from the designer to the final consumer wherever the participants

of the production chain be located.

5 References

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<http://www.chromashare.com>. Acesso em: 13 Aug. 2010.

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<http://www.datacolor.com/learningarticles/Reflectance%20in%20Perspective.pdf>. Acesso em:

13 Aug. 2010a.

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<http://www.datacolor.com/software/envision/>. Acesso em: 13 Aug. 2010b.

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(AIC), 9., Rochester, NY, 2001. SPIE v. 4421, p. 646-649, 2002.

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HIRSCHLER, Robert. Colour communication in industry from design to product - with special

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Colourists, 2011. (in preparation).

ICI Instrumental Match Prediction. Manchester: ICI Dyestuffs Division, 1963.

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12, p. 516-520, Dec. 1992.

RHODES, Peter A.; LUO, M. Ronnier. A system for WYSIWYG colour communication. Displays.

Amsterdam, v. 16, n. 4, p. 213-221, May 1996.

SCHANDA, János. CIE colorimetry. In: SCHANDA, János. Colorimetry: understanding the CIE

System. Hoboken: John Wiley & Sons, 2007. 25-78

VASCONCELLOS, James R. Supply chain management of color & appearance: evolution vs.

revolution. AATCC Review. Research Triangle Park, N.C., USA, v. 1, n. 6, p. 14-18, June 2001.

VERIVIDE. Disponível em: <www.verivide.com>

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Aug. 2010.

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Biographical Notes

Robert Hirschler graduated at the Technical University of Budapest

(Hungary) in textile chemistry and has been involved in textile dyeing,

finishing and applied colorimetry for over 40 years. He has been working

for CETIQT as technical advisor since 1988, for 15 years as a consultant of

the United Nations Industrial Development Organization. He is Chair of

two CIE Technical Committees: TC1-44 (Practical Daylight Sources for

Colorimetry) and TC1-77 (Improvement of the CIE Whiteness and Tint

Equations) and also that of the AIC Study Group on Colour Education. Email address: [email protected]

Curriculum at Lattes Platform: http://lattes.cnpq.br/0080512317658424

http://www.verivide.com/�

http://en.wikipedia.org/wiki/Color_management�

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