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doi: 10.1111/cote.12162

A multispectral imaging approach to colour measurement and colour matching of single yarns without winding

Coloration Technology

Lin Luo,a Hui-Liang Shen,b Si-Jie Shaoa and John H Xina,* a

Institute of Textiles and Clothing, The Hong Kong Polytechnic University, Chow Yei Ching Building, Hung Hom, Kowloon, Hong Kong Email: [email protected]

b

Department of Information Science and Electronic Engineering, Zhejiang University, 38 Zheda Road, Hangzhou, China

Society of Dyers and Colourists

Received: 15 August 2014; Accepted: 1 May 2015 This paper investigates a multispectral imaging approach to colour measurement and colour matching of single yarns. The small size of a single yarn makes it impossible for spectrophotometers directly to acquire its spectral reflectance. Multispectral imaging systems, on the other hand, have the potential to measure the reflectance of single yarns as they can record both the spectral and the spatial information of a sample. A multispectral imaging system, namely imaging colour measurement, has been developed to conduct colour measurement of single yarns. A single yarn is first detected from backgrounds by a modified K-means clustering method. The reflectance of the single yarn is then specified by an averaging method. Comparative experiments based on 100 pairs of single yarns and corresponding yarn windings show that the reflectance magnitude of a single yarn acquired by imaging colour measurement is smaller than that of corresponding yarn winding measured by a Datacolor 650 spectrophotometer. Experiments on 16 single yarns show that the repeatability and spatial reproducibility of the imaging colour measurement system in measuring a single yarn colour are 0.1185 and 0.2827 CMC(2:1) units. A colour matching comparison experiment (pass or fail), using 24 pairs of single yarns and corresponding pairs of solid-colour yarn dyed fabrics, shows that single yarns measured by imaging colour measurement can achieve similar colour matching results to solid-colour yarn dyed fabrics measured by the Datacolor 650 spectrophotometer, with degrees of similarity of 87.5 and 83.3% when the CMC(2:1) and CIE2000(2:1:1) colour difference formulas are employed.

Introduction In the textile and garment industries, colour measurement and colour matching of yarn dyed fabrics are carried out on spectrophotometers. However, a spectrophotometer can only acquire colours of solid-colour samples, such as solid-colour yarn dyed fabrics and yarn windings. In order to carry out colour measurement of multicolour yarn dyed fabrics on a spectrophotometer, weft and warp yarns of the fabrics must be manually separated and individually woven into solid-colour yarn dyed fabrics or yarn windings. This process is inefficient and prone to error owing to inconsistency in preparing these samples [1–3]. Another limitation of spectrophotometers is that the spectrophotometric measurement results of fabrics are dramatically influenced by their woven structures and areal densities [4–7]. According to the reflection model proposed by Luo et al. [2], the light reflected by a yarn dyed fabric is affected by three factors: surface texture, interreflection between neighbouring yarns, and system illuminant occlusion. The influence of texture on colour is formulated by a geometric term, which is determined by the incident angle of light and would result in the intensity of the reflected light changing with surface positions. Interreflection between neighbouring yarns would yield ambient illumination. Colour shift occurs when a yarn is cross-woven by different coloured yarns. System illuminant occlusion stems from masking by neighbouring yarns and is modelled by a block parameter. All of these three factors are influenced by the woven structure and areal density of a yarn dyed fabric. In contrast, the light reflected by a single yarn is not affected by surface texture and interreflection. While single yarns 342

have much simpler structures than yarn dyed fabrics, spectrophotometers cannot directly acquire the colour of a single yarn but that of corresponding yarn pad, yarn skein, or yarn winding [8–10]. A spectrophotometer can only measure the average reflectance of a sample area presented in the aperture [11]. A single yarn is too small to cover the entire aperture of a spectrophotometer. Instead, single yarns with the same colour are stapled as a pad, a skein, or yarn winding, and its spectrophotometric colour is measured as the colour of corresponding single yarn [8]. Uniformity of these formers is of importance, and commercial machines are usually used to wind specimens automatically [9]. With the development of digital imaging technology, multispectral imaging (MSI) systems [12,13] are being adopted to measure the colour of a fabric sample. An MSI system can provide not only the spectral information but also the spatial information of a sample. The spatial information alleviates the limitation on the size of a sample when acquiring its colour. Thus, MSI systems have the potential to measure directly the colour of a single yarn without winding. In this paper, a novel multispectral imaging approach is proposed for accurate acquisition of the colours of single yarns without winding. A single yarn is first detected from backgrounds by a modified K-means clustering method. The reflectance of the single yarn is then specified as the mean reflectance of all the pixels on the yarn.

Experimental Step 1: Segment single yarns from backgrounds As shown in Figure 1a, a single yarn is fixed on a black platform to keep stretched. The modified K-means

© 2015 The Authors. Coloration Technology © 2015 Society of Dyers and Colourists, Color. Technol., 131, 342–351

Luo et al. Colour measurement & matching of single yarns

(a)

(b)

(c)

(d)

Figure 1 Example of single yarn segmentation: (a) a single yarn is selected manually to measure its colour, where the yellow rectangle represents the selected segment of the single yarn; (b) the unprocessed image of the selected single yarn; (c) the binary segmentation results, where the white pixels represent the single yarn; (d) the segmentation results in RGB format [Colour figure can be viewed in the online issue, which is available at wileyonlinelibrary.com.]

clustering method proposed by Luo et al. [3] is employed to segment the single yarn from backgrounds. The number of clusters is 2, i.e. pixels are grouped into two classes: background or single yarn. The distance between a pixel and the mean of a cluster is measured by the CIELAB colour difference. The initial means are determined by the random partition method [14]. ð1Þ ð1Þ ð1Þ Given an initial set of k means ðm1 ; m2 ; . . .;mk Þ, image pixels (x1, x2, . . ., xn) are partitioned into sets S = {s1, s2, . . ., sk} (k ≤ n) by alternating between an assignment step and an update step: Assignment step ðtÞ

ðtÞ

ðtÞ

Si ¼ fxp :DEðxp ; mi Þ  DEðxp ; mj Þ; 81  j  kg

ð1Þ

Update step ðtþ1Þ

mi

1 X ¼   xj ðtÞ Si  xj 2SðtÞ

ð2Þ

i

where DE(x, m) denotes the CIELAB colour difference between the pixel x and the cluster mean m. Figure 1c,d show the binary and RGB-format segmentation results of Figure 1b by the modified K-means clustering method.

Step 2: Specify the reflectance of single yarns According to the reflection model proposed by Luo et al. [2], the spectral response of a multispectral imaging system to a yarn dyed fabric can be modelled as Rb ðk; pC ; qC Þ ¼ mb ðpY ; qY ÞHðpY ; qY ÞR1 ðkÞ þ mb ðpY ; qY ÞAðpY ; qY ÞR1 ðkÞR2 ðkÞ

ð3Þ

where Rb(k, pC, qC) denotes the measured reflectance of the pixel (pC, qC), (pY, qY) is the position on the yarn dyed fabric surface corresponding to (pC, qC), and R1(k) and R2(k) represent the nominal reflectance of the measured yarn and its neighbouring yarn. mb(pY, qY), H(pY, qY), and A(pY, qY) express the influences of fabric surface texture, system illuminant, and interreflection on the measured reflectance. For a single yarn fixed on a black platform, the model can be simplified as Rb ðk; pC ; qC Þ ¼ mb ðpY ; qY ÞHðpY ; qY ÞR1 ðkÞ  1 ðkÞ ¼ ½mb ðpY ; qY ÞHðpY ; qY ÞjR1 ðkÞjR

ð4Þ

where mb ðpY ; qY ÞHðpY ; qY ÞjR1 ðkÞj is the magnitude of the  1 ðkÞ denotes the normalised measured reflectance, and R nominal reflectance, which defines the direction of the measured reflectance in the reflectance space.

© 2015 The Authors. Coloration Technology © 2015 Society of Dyers and Colourists, Color. Technol., 131, 342–351

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The expression in Eqn (4) defines a set of lines with identical direction but different magnitude. The direction of these lines is determined by the normalised reflectance  1 ðkÞ. Their magnitude depends on the geometric term R mb(pY, qY), the occlusion coefficient H(pY, qY), and the magnitude of the nominal reflectance jR1 ðkÞj. Note that the geometric term in Eqn (4) is defined as mb(pY, qY) = cos(h), where h denotes the incident angle at the surface position (pY, qY) of a yarn [2]. For pixels at the edge area of a single yarn surface, the geometric term approaches 0 because of large incident angles. In contrast, the geometric term comes up to 1 for pixels in the central area of a single yarn. As a result, reflectance of pixels on a single yarn surface shifts in the reflectance space. Equivalent to the colour acquired by a spectrophotometer [11], an averaging method is proposed to specify the reflectance of a single yarn measured by a multispectral imaging system: P Rb ðk; pC ; qC Þ RðkÞ ¼ ð5Þ NpC ;qC where R(k) and NpC ;qC denote the specified reflectance and the total number of pixels on the single yarn. Figure 2 illustrates the specified reflectance of the single yarn shown in Figure 1d, where the blue curves represent the reflectance of pixels on the single yarn. The red curve shows the specified reflectance by the averaging method. The reflectance variation among pixels can be considered as the result of the influence of the geometric term mb(pY, qY).

1

Reflectance

0.8 0.6 0.4 0.2 0 400

450

500 550 600 Wavelength, nm

650

700

Figure 2 The reflectance curves of all the pixels on the single yarn shown in Figure 1d and the specified reflectance. The blue curves represent the reflectance of all the pixels on the single yarn; the red curve denotes the specified reflectance of the single yarn by the averaging method [Colour figure can be viewed in the online issue, which is available at wileyonlinelibrary.com.]

Results and discussion Multispectral imaging system introduction An MSI system, namely imaging colour measurement (ICM) [1–3], was developed to achieve colour measurement of single yarns. The ICM system consisted of a monochrome digital camera, a filter wheel with 16 narrowband filters, an autofocus step motor, and a circular light source. The monochrome digital camera captured an image with 1040*1392 pixels. The filter wheel split the spectrum of visible light into 16 bands. The step motor controlled the focus of the camera by rotating its aperture. The circular light source provided a 45°/0° CIE D65 illumination, which can eliminate the influence of gloss on colour. The focus of the monochrome camera was autoadjusted by the method proposed by Shen et al. [15]. The reflectance of a single yarn sample was reconstructed by the method proposed by Shen et al. [12,13]. Some preliminary tests were carried out to ensure the good performance of the ICM system in colour measurements of single yarns. The repeatability of ICM in measuring National Institute of Standards and Technology (NIST) white tiles was 0.03CMC(2:1)units,wherecolourmeasurementswerecarried out every 15 min in a period of 480 min. The systematic illumination uniformity of ICM, including illumination uniformity of light source and photoresponse non-uniformity (PRNU)ofcamera,wastestedbyNISTwhitetiles.Thecaptured images of the NIST white tiles were separated into nine mosaic regions,andtheCMC(2:1)colourdifferencebetweenthecentral region and other regions was calculated. The average and maximumcolourdifferenceswere0.01and0.1CMC(2:1)units. The accuracy of the ICM system was measured by the interinstrument agreement between ICM and a benchmark reflection spectrophotometer Datacolor 650 (D650) in terms of spectral reflectance root mean square (RMS) error and CMC(2:1) colorimetric accuracy. The spectral reflectance RMS error between ICM and D650 in measuring a sample is defined as sffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi 1X k k Erefl ¼ ðr  rD650 Þ2 ð6Þ n k ICM k where Erefl denotes the spectral reflectance RMS error, rICM k and rD650 represent the reflectance values of the kth band acquired by the ICM and D650 systems, and n expresses the number of bands. The Digital Colorchecker SG from GretagMacbeth (USA) was used to test the interinstrument agreement between ICM and D650. The average and maximum spectral reflectance accuracies of ICM were 0.0024 and 0.0089 RMS. The average and maximum colorimetric accuracies of ICM were 0.23 and 0.62 CMC(2:1) units. The technical specification of the ICM system is summarised in Table 1.

Table 1 The technical specification of the ICM system Repeatability (on NIST white tiles) Systematic uniformity of illumination (on NIST white tiles) Interinstrument agreement between ICM system and benchmark reflection spectrophotometer (on Digital Colorchecker SG)

Optical configuration Spectral range

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Average: 0.03 CMC(2:1) units Maximum: 0.1 CMC(2:1) units Average: 0.01 CMC(2:1) units Average spectral reflectance accuracy: 0.0024 RMS errors Maximum spectral reflectance accuracy: 0.0089 RMS errors Average colorimetric accuracy: 0.23 CMC(2:1) units Maximum colorimetric accuracy: 0.62 CMC(2:1) units 45°/0° 400–700 nm

© 2015 The Authors. Coloration Technology © 2015 Society of Dyers and Colourists, Color. Technol., 131, 342–351

Luo et al. Colour measurement & matching of single yarns

Colour measurement comparison between single yarns and corresponding yarn windings The first experiment compared the multispectral imaging reflectance of single yarns and the spectrophotometric reflectance of corresponding yarn windings, using 100 pairs of single yarns and yarn windings. The material of these samples was cotton, and their yarn count was 500 dtex. A single yarn was carefully wound on a card to constitute the corresponding yarn winding according to the standard [9], as shown in Figure 3b. The reflectance of single yarns and yarn windings was acquired by the ICM system and a Datacolor 650 (D650) spectrophotometer respectively. The spectrophotometric measurements were conducted under a 1964 CIE standard observer. The specular-component-excluded (SCE) and UV-excluded modes were applied to eliminate the influences of specular light and UV on samples. Figures 3c and d show the multispectral imaging reflectance of the 100 single yarns and the spectrophotometric reflectance of the corresponding yarn windings. Note that the reflectance range of single yarns is smaller than that of yarn windings. In order quantitatively to compare the reflectance of a single yarn and corresponding yarn winding, the reflectance angle and magnitude were calculated [11]:   RYW ðkÞ  RSY ðkÞ h ¼ cos1 ð7Þ kRYW ðkÞkkRSY ðkÞk and jRjSY

sffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi sffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi n n X X 2 i i Þ2 ¼ ðrSY Þ or jRjYW ¼ ðrYW i¼1

represent the reflectance magnitude of a single yarn and i i corresponding yarn winding, rSY and rYW express the reflectance value of a single yarn and corresponding yarn winding in the ith band, and n denotes the number of spectral bands. Table 2 shows the reflectance angle and reflectance magnitude difference between single yarns and corresponding yarn windings. The average reflectance angle of the 100 pairs of single yarns and yarn windings is 2.77°, with a standard deviation of 1.85°, which implies that the reflectance direction of the single yarns and corresponding yarn winding is different. Note that the maximum reflectance magnitude difference between single yarns and yarn windings is 0.03, which indicates that the reflectance magnitude of yarn windings is larger than that of corresponding single yarns for all the samples. This should stem from interreflection between neighbouring yarns in yarn windings. However, interreflection does not exist in single yarns, as shown in Figure 3a. Repeatability and spatial reproducibility The second experiment checked the repeatability and reproducibility of ICM in colour measurement of single yarns. Repeatability is the ability of an instrument in repeatedly measuring a sample under the same conditions, such as the same operator and the same measurement Table 2 Reflectance angles (h) and reflectance magnitude difference ðjRjSY  jRjYW Þ between single yarns and corresponding yarn windings

ð8Þ

i¼1

where RYW(k) and RSY(k) denote the reflectance of a single yarn and corresponding yarn winding, jRjSY and jRjYW

h jRjSY  jRjYW

(a)

Min

Max

SD

2.77° 0.39

2.25° 0.29

0.68° 1.47

14.18° 0.03

1.85° 0.33

1 0.8 Reflectance

0.8 Reflectance

Median

(b)

1

0.6 0.4

0.6 0.4 0.2

0.2 0 400

Mean

500 600 Wavelength, nm (c)

700

0 400 450 500 550 600 650 700 Wavelength, nm (d)

Figure 3 Example of single yarns and corresponding yarn windings and their reflectance measured by the ICM and D650 systems: (a) example of single yarns; (b) example of corresponding yarn windings; (c) reflectance curves of the 100 single yarns measured by ICM; (d) reflectance curves of the corresponding yarn windings acquired by D650 [Colour figure can be viewed in the online issue, which is available at wileyonlinelibrary.com.] © 2015 The Authors. Coloration Technology © 2015 Society of Dyers and Colourists, Color. Technol., 131, 342–351

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Luo et al. Colour measurement & matching of single yarns

reproducibility of the ICM multispectral imaging system in measuring single yarn colour. The material of these single yarns was cotton. The yarn count of these single yarns was 500 dtex. As shown in Figure 4b, two single yarn segments from the same cone were placed adjacently to assess the spatial reproducibility of ICM. The left and right single yarn segments in a colour centre C were labelled as C1 and C2. For example, the two red single yarns in Figure 4b were named Red 1 (left) and Red 2 (right). These 16 single yarns were measured by ICM every 30 min for a period of 810 min. The colour difference between each measurement and the mean of measurements were calculated by the CMC (2:1) formula. The repeatability and spatial reproducibility of ICM in measuring the colours of single yarns are shown in Table 3. For the 16 single yarns, the average MeanCDM of repeatability is 0.1185 CMC(2:1) units. The average MaxCDM and MinCDM of repeatability are 0.3353 and 0.0026 CMC(2:1) units. ICM has the best repeatability performance in measuring the purple single yarns (Purple 1 and Purple 2), i.e. 0.0906 and 0.0906 CMC(2:1) units. The repeatability of ICM in measuring the red single yarns (Red 1 and Red 2) is worst, 0.1591 and 0.1591 CMC(2:1) units, results that are relatively larger than the measurement results of purple single yarns. This implies that the repeatability of ICM is better in measuring colours of purple single yarns than in measuring colours of red single yarns. The spatial reproducibility of ICM in measuring the colours of these 16 single yarns is 0.2827 CMC(2:1) units, within the range of 0.1768 and 0.4043 CMC(2:1) units. ICM has the best spatial reproducibility performance in measuring the orange single

procedures [16]. It is quantified as the mean colour difference between each measurement and the mean of measurements (MeanCDM) [17]: N P

DEi MeanCDM ¼ i¼1 N

ð9Þ

where N is the number of measurements, and DEi denotes the colour difference between the ith measurement and the mean of measurements. The maximum and minimum colour differences between each measurement and the mean of measurements (MaxCDM and MinCDM) are also considered in this study. These are defined as  MaxCDM ¼ maxðDE1 ; DE2 ; . . .;DEN Þ ð10Þ MinCDM ¼ minðDE1 ; DE2 ; . . .;DEN Þ Reproducibility is similar to repeatability, except that some aspects of the measurement conditions have changed. For example, the same measurement procedures are used when the operator or the laboratory is changed [16]. The spatial reproducibility is one of most important concepts when a multispectral imaging system is used to measure the colour of a sample. Spatial reproducibility is defined as how close the measurements of a sample are when the same measurement procedures are used but the sample is placed at different positions. Spatial reproducibility is also qualified as MeanCDM, MaxCDM, and MinCDM. As shown in Figure 4a, 16 single yarns in eight colour centres were used to evaluate the repeatability and spatial

Green

Light Grey

Purple

Dark Grey

Brown

Red

Blue

Orange

(a)

(b) Figure 4 The 16 single yarn samples used to conduct repeatability and spatial reproducibility experiments: (a) the colour centres of these yarns; (b) the arrangement of these yarns [Colour figure can be viewed in the online issue, which is available at wileyonlinelibrary.com.]

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© 2015 The Authors. Coloration Technology © 2015 Society of Dyers and Colourists, Color. Technol., 131, 342–351

Luo et al. Colour measurement & matching of single yarns

Table 3 Repeatability and spatial reproducibility of ICM in measuring the 16 single yarns shown in Figure 4 Repeatability

Green 1 Green 2 Purple 1 Purple 2 Brown 1 Brown 2 Red 1 Red 2 Light Grey 1 Light Grey 2 Dark Grey 1 Dark Grey 2 Blue 1 Blue 2 Orange 1 Orange 2 Average

Spatial reproducibility

MeanCDM

MaxCDM

MinCDM

MeanCDM

MaxCDM

MinCDM

0.1150 0.1276 0.0906 0.0906 0.1090 0.1090 0.1591 0.1591 0.1376 0.1376 0.1166 0.1166 0.1137 0.1137 0.0999 0.0999 0.1185

0.3889 0.3889 0.3010 0.3010 0.2032 0.2032 0.4338 0.4338 0.3684 0.3684 0.3461 0.3461 0.3826 0.3826 0.2586 0.2586 0.3353

0.0232 0.0232 0.0225 0.0225 0.0191 0.0191 0.0267 0.0267 0.0260 0.0260 0.0293 0.0293 0.0064 0.0064 0.0278 0.0278 0.0226

0.2756 0.2756 0.3163 0.3163 0.2724 0.2721 0.2817 0.2818 0.3170 0.3164 0.3396 0.3385 0.2801 0.2801 0.1798 0.1798 0.2827

0.3111 0.3111 0.5006 0.5005 0.5642 0.5634 0.3924 0.3924 0.4310 0.4302 0.3842 0.3829 0.4203 0.4203 0.2320 0.2320 0.4043

0.2514 0.2514 0.1570 0.1570 0.0868 0.0868 0.1710 0.1712 0.2200 0.2193 0.2552 0.2541 0.1478 0.1478 0.1260 0.1260 0.1768

yarns (Orange 1 and Orange 2), i.e. 0.1798 and 0.1798 CMC (2:1) units. The slight difference in repeatability and spatial reproducibility of ICM in measuring single yarns with different colours can be considered to be a result of the difference in preparing samples, such as the tension difference of single yarns when they are fixed on the black platform. Table 3 shows that the ICM multispectral imaging system has good repeatability and spatial reproducibility in measuring single yarn colour. Instrumental colour matching experiment Colour matching [18] is a vital process in ensuring continuity of colour from a master standard to a subsequent batch. Colour matching between standard and batch fabrics can be conducted by two methods: instrumental evaluation and visual assessment. The instrumental method employs a colour measurement instrument to measure the colours of standard and batch samples. Instrumental colour matching is achieved by comparing the colour difference between the standard and batch samples with a tolerance predetermined by users. If the measured colour difference is smaller than the tolerance, the colour matching result is ‘pass’, i.e. the colour of the batch sample matches that of the standard sample, and vice versa. Visual colour matching evaluates the colour difference between standard and batch samples by the naked eye in a light cabinet. The visual colour matching result is ‘pass’ when the inspector cannot perceive any difference between standard and batch samples, and vice versa. The instrumental method is more accurate than the visual method, as the latter is a subjective process. Inconsistent colour matching results may exist among different inspectors. Spectrophotometers enjoy widespread use in the colour matching of fabrics. However, a spectrophotometer cannot directly carry out colour matching between single yarns, but solid-colour yarn dyed fabrics or yarn windings. In contrast, colour matching between standard and batch single yarns can be achieved by the ICM multispectral imaging system. Therefore, a third experiment compared colour matching based on multispectral imaging measurement of single yarns and spectrophotometric measurements of solid-colour yarn dyed fabrics.

Twenty-four solid-colour yarn dyed fabrics and corresponding single yarns were used to conduct the colour matching comparison experiment. The linear and surface densities of the solid-colour fabric samples were 250 dtex and 80*60 threads per inch (TPI) in the warp and weft directions respectively. The material of these samples was cotton. A Datacolor 650 (D650) desktop spectrophotometer was used to acquire the reflectance of the solid-colour yarn dyed fabrics. The measurements were conducted under the 1964 CIE standard observer. The specular-component-excluded (SCE) and UV-excluded modes were applied to eliminate the influences of specular light and UV on samples. Based on the measured spectrophotometric reflectance of the 24 solidcolour yarn dyed fabrics, dye formulas to reproduce them were predicted by the D650 system, and 24 solid-colour batch yarn dyed fabrics were dyed. The corresponding single yarns of the standard and batch yarn dyed fabrics were collected as standard and batch single yarns. The reflectance of the single yarns was acquired by the ICM multispectral imaging system. The colour difference between standard and batch samples (solid-colour yarn dyed fabrics and corresponding single yarns respectively) was calculated by the CMC(2:1) and CIE2000 (2:1:1) formulas under the CIE standard illuminant D65. The tolerance to determine colour matching results (pass or fail) in this experiment was set to 1.0 CMC(2:1) units and CIE2000 (2:1:1). The reflectance values of the standard yarn dyed fabrics and corresponding single yarns are shown in Figure 5. Lightness difference (ΔL*) and hue difference (Δa* and Δb*) between standard and batch samples of fabrics and single yarns were first compared. As shown in Table 4, the ΔL*, Δa*, and Δb* values between the standard and batch yarn dyed fabrics measured by the D650 spectrophotometer are in the ranges [1.25 0.50], [1.89 1.24], and [3.35 1.34], with means of 0.25, 0.04, and 0.02 respectively. Accordingly, the ΔL*, Δa*, and Δb* values between the standard and batch single yarns measured by ICM are in the ranges [1.81 0.75], [1.18 0.59], and [0.94 0.93], with means of 0.32, 0.30, and 0.04 respectively. Note that the range of hue difference (Δa* and Δb*) between standard and batch fabrics measured by D650 is larger than that of corresponding single yarns measured by ICM, which can be

© 2015 The Authors. Coloration Technology © 2015 Society of Dyers and Colourists, Color. Technol., 131, 342–351

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1

1

0.8

0.8 Reflectance

Reflectance

Luo et al. Colour measurement & matching of single yarns

0.6 0.4

0.6 0.4 0.2

0.2 0 400 450 500 550 600 650 700 Wavelength, nm

0 400 450 500 550 600 650 700 Wavelength, nm

(a)

(b)

Figure 5 The reflectance of the 24 standard yarn dyed fabrics and corresponding single yarns: (a) the reflectance of the 24 standard yarn dyed fabrics; (b) the reflectance of the corresponding single yarns [Colour figure can be viewed in the online issue, which is available at wileyonlinelibrary.com.]

Table 4 Lightness difference (ΔL*) and hue difference (Δa* and Δb*) between standard and batch samples of fabrics and single yarns. The colours of fabrics and single yarns were measured by D650 spectrophotometer and ICM respectively Yarn dyed fabrics

ΔL* Δa* Δb*

Single yarns

Mean

Median

Max

Min

SD

Mean

Median

Max

Min

SD

0.25 0.04 0.02

0.21 0.04 0.05

0.50 1.24 1.34

1.25 1.89 3.35

0.49 0.55 0.94

0.32 0.30 0.04

0.38 0.29 0.09

0.75 0.59 0.93

1.81 1.18 0.94

0.67 0.39 0.47

considered to be the result of the influence of fabric structure on fabric colour. The spectrophotometric colours of yarn dyed fabrics are influenced not only by the linear density of the yarns but also by the areal density of the fabrics. However, the multispectral imaging colours of single yarns are only affected by the linear density of the yarns. The CMC(2:1) and CIE2000(2:1:1) colour differences between standard and batch samples of single yarns and yarn dyed fabrics are shown in Figure 6. The black lines indicate that the same colour difference is acquired by single yarns and corresponding yarn dyed fabrics. The closer a dot to the black lines, the closer is the colour difference between a pair of standard and batch single yarns to the colour difference between corresponding standard and batch fabrics. Dots above the black lines imply that the colour difference of yarn dyed fabrics is larger than that of corresponding single yarns,

and vice versa. As shown in Figure 6a, five blue dots are above but close to the black line, which implies that the CMC(2:1) colour difference of these five pairs of standard and batch yarn dyed fabrics is slightly larger than that of the corresponding five pairs of single yarns. Sixteen blue dots are below the black line, which indicates that the colour difference of these 16 pairs of yarn dyed fabrics is smaller than that of corresponding pairs of single yarns. For the yarn dyed fabrics and single yarns shown as blue dots in Figure 6a, the same colour matching results are achieved when the tolerance is set at 1.0 CMC(2:1) units, i.e. 20 pairs of standard and batch samples of yarn dyed fabrics and corresponding single yarns obtain a ‘pass’ result, and one pair of fabric and corresponding single yarn samples have a ‘fail’ result. However, three pairs of standard and batch samples of yarn dyed fabrics and single yarns yield different colour matching results, as shown by the 2

2.5 1.5 Fabric

Fabric

2 1.5

1

1 0.5 0.5 0

0

0.5

1 1.5 2 Singe yarn (a)

2.5

0

0

0.5

1 Singe yarn

1.5

2

(b)

Figure 6 The colour matching comparison results [CMC(2:1) and CIE2000(2:1:1)] between single yarns measured by ICM and solid-colour yarn dyed fabrics measured by D650: (a) colour matching results measured by CMC(2:1) colour difference; (b) colour matching results measured by CIE2000(2:1:1) colour difference. The horizontal and vertical axes represent the CMC(2:1) or CIE2000(2:1:1) colour difference between standard and batch samples of single yarns and fabrics measured by the ICM and D650 systems. The black lines denote that the same CMC(2:1) or CIE2000(2:1:1) colour difference is measured by ICM and D650 [Colour figure can be viewed in the online issue, which is available at wileyonlinelibrary.com.]

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three red dots in Figure 6a. The colour difference of the three pairs of single yarns measured by ICM is 0.34, 0.35, and 0.70 CMC(2:1) units, which is smaller than the colour matching tolerance of 1.0 CMC(2:1) unit. In contrast, the colour difference of the three pairs of corresponding yarn dyed fabrics measured by D650 is 1.27, 1.90, and 1.38 CMC(2:1) units, which is larger than the tolerance of 1.0 CMC(2:1) units. As a consequence, the colour matching results from single yarns are ‘pass’, but ‘fail’ from corresponding solid-colour yarn dyed fabrics. Figure 6b shows the colour matching results in terms of CIE2000(2:1:1) colour difference. As shown by the blue dots, 20 pairs of standard and batch samples of yarn dyed fabrics and corresponding single yarns yield the same colour matching results (pass) when the tolerance is set at 1.0 CIE2000(2:1:1) units. However, different colour matching results are found in four pairs of yarn dyed fabrics and single yarns, as shown by the four red dots in Figure 6b. The colour matching results of the four pairs of yarn dyed fabrics are ‘fail’, whereas opposite matching results are obtained by corresponding single yarns. The different colour matching results yielded by single yarns and corresponding yarn dyed fabrics can be considered to be a result of the influence of fabric structure on colour. The fabric structure of a yarn dyed fabric, such as areal density and yarn direction, can affect the spectrophotometric colour of the fabric. Therefore, it is possible that the colour difference between standard and batch fabrics is larger than the colour matching tolerance, but that of the corresponding single yarns is smaller than the tolerance. We can conclude from Figure 6 that single yarns measured by multispectral imaging systems can achieve similar colour matching results to yarn dyed fabrics measured by spectrophotometers, where the degrees of similarity are 87.5 and 83.3% for the CMC(2:1) and CIE2000(2:1:1) colour difference formulas.

Conclusions A novel multispectral imaging approach for accurate colour measurement and colour matching of single yarns without winding is developed in this study. Firstly, a single yarn is segmented from backgrounds in multispectral images by a modified K-means clustering method. Secondly, the multispectral imaging reflectance of the single yarn is specified by an averaging method. A multispectral imaging system, namely imaging colour measurement (ICM), has been developed to evaluate the proposed approach. The interinstrument agreement between ICM and a benchmark spectrophotometer Datacolor 650 is 0.23 CMC(2:1) units to measure the colour of the Digital Colorchecker SG from GretagMacbeth. 100 pairs of single yarns and corresponding yarn windings were used to compare the reflectance of single yarns and yarn windings measured by ICM and a spectrophotometer. Experimental results show that the reflectance magnitude of a single yarn acquired by ICM is smaller than that of corresponding yarn winding measured by a Datacolor 650 spectrophotometer. An experiment using 16 single yarns in eight colour centres shows that the repeatability and spatial reproducibility are 0.1185 and 0.2827 CMC(2:1) units to measure single yarn colour. A colour matching comparison experiment between ICM and

the Datacolor 650 spectrophotometer was conducted using 48 pairs of standard and batch solid-colour yarn dyed fabrics and 48 corresponding pairs of single yarns. Experimental results show that single yarns measured by ICM can achieve similar colour matching results to solid-colour yarn dyed fabrics measured by the Datacolor 650 spectrophotometer, where the degrees of similarity are 87.5 and 83.3% when the CMC(2:1) and CIE2000(2:1:1) colour difference formulas are applied. While these results are promising and useful, there is still much work to be done. Firstly, the proposed K-means segmentation method should be compared with other segmentation methods, such as thresholding methods. Secondly, reflectance specification methods of a single yarn from multispectral images should be further explored. Thirdly, colour measurement comparison among single yarns mounted on black, white, and neutral grey backgrounds should be conducted to analyse the influence of background colour on the colours of single yarns acquired by a multispectral imaging system. Finally, the relationship between multispectral imaging colours of single yarns and spectrophotometric colours of corresponding yarn windings or solidcolour yarn dyed fabrics should be studied.

Acknowledgements The authors thank the anonymous reviewers for their helpful comments. This work was supported by the Innovation and Technology Commission of the Hong Kong SAR Government (the HKRITA project ITP/001/10TP and ITP/048/13TP), the Hong Kong Polytechnic University, and the National Natural Science Foundation of China under grant 61371160.

References 1. L Luo, S J Shao, H L Shen and J H Xin, Color. Technol., 129 (2013) 389. 2. L Luo, H L Shen, S J Shao and J H Xin, Color. Technol., 131 (2015) 120. 3. L Luo, H L Shen, S J Shao and J H Xin, Color. Technol., 131 (2015) 165. 4. M Akgun, B Becerir and H R Alpay, Fiber Polym., 15 (2014) 126. 5. K Mathur, A M Seyam, D Hinks and R A Donaldson. Color. Technol., 124 (2008) 48. 6. H Gabrijelcic and K Dimitrovski. Fibres Text. East. Eur., 12 (2004) 32. 7. H Gabrijelcic and K Dimitrovski, Color. Technol., 125 (2009) 74. 8. C E Garland, Color Technology in the Textile Industry (Research Triangle Park, NC: AATCC, 1983) 65. 9. Instrumental colour measurement of textiles – Method (London: BSI, 2006). 10. B Philips-Invernizzi, D Dupont and C Caze, Color Res. Appl., 27 (2002) 191. 11. L Luo, K M Tsang, H L Shen, S J Shao and J H Xin, Color Res. Appl., Doi: 10.1002/col.21923. 12. H L Shen, P Q Cai, S J Shao and J H Xin, Opt. Express, 15 (2007) 15 545. 13. H L Shen, J H Xin and S J Shao, Opt. Express, 15 (2007) 5531. 14. G Hamerly and C Elkan, Proc. Int. Conf. Information and Knowledge Management, McLean, VA (2002) 600. 15. H L Shen, Z H Zheng, W Wang, X Du, S Shao and J H Xin. Appl. Opt., 51 (2012) 2616. 16. K Nassau, Color for Science, Art and Technology (Amsterdam: North Holland, 1998) 82. 17. R W G Hunt and M R Pointer, Measuring Colour (New York, NY: Wiley, 2011) 197. 18. G A Klein, Industrial Color Physics (New York, NY: Springer, 2010) 252.

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Appendix 1 The reflectance angles (h) between single yarns and corresponding yarn windings and their reflectance magnitude (|R|SY and |R|YW) in the colour measurement comparison experiment

Sample

h

|R|SY

|R|YW

Sample

h

|R|SY

|R|YW

Sample

h

|R|SY

|R|YW

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34

5.21 5.66 3.81 2.86 5.31 3.85 3.49 3.79 2.05 1.34 4.72 6.87 5.67 8.13 4.77 3.84 4.73 4.69 5.44 5.26 2.06 3.73 4.79 4.05 4.32 1.79 2.02 1.55 1.08 2.53 2.16 1.72 1.70 3.13

2.47 2.23 1.70 3.00 2.45 1.53 1.44 1.69 0.94 0.68 1.37 2.17 2.12 2.69 2.15 1.38 1.80 2.24 2.47 2.21 3.21 2.10 2.18 2.81 2.68 1.76 2.24 1.00 1.08 2.44 1.46 1.59 1.59 1.10

3.36 3.14 2.26 4.04 3.25 2.03 1.90 2.24 1.08 0.84 1.75 3.05 2.88 3.35 2.97 1.67 2.66 2.98 3.30 3.18 4.68 2.68 2.80 3.94 3.76 2.18 2.67 1.13 1.47 3.17 1.63 1.77 1.89 1.26

35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68

1.66 2.90 1.83 1.71 1.42 1.31 14.18 1.60 3.54 1.34 1.10 1.67 1.32 2.16 2.94 1.24 2.64 1.35 2.88 1.73 0.99 2.31 2.60 2.92 2.29 2.56 2.18 2.53 1.21 2.56 0.91 2.20 0.94 1.26

0.60 2.68 1.45 1.27 0.57 0.79 0.79 2.05 3.04 0.51 0.47 0.54 0.32 0.40 1.15 0.39 2.07 0.84 1.46 1.07 0.84 2.22 2.00 1.81 2.99 2.77 2.19 2.08 0.99 2.26 0.70 1.76 0.42 0.53

0.65 3.26 1.78 1.54 0.62 0.89 1.16 2.44 4.18 0.55 0.53 0.65 0.36 0.49 1.44 0.46 2.47 0.96 1.74 1.26 0.93 2.71 2.38 2.05 4.10 3.72 2.91 2.50 1.11 2.92 0.80 1.99 0.46 0.61

69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100

1.94 2.65 1.90 1.84 0.82 1.04 1.18 3.28 3.63 2.18 2.08 1.04 4.11 1.19 3.24 3.34 2.36 4.11 2.52 3.77 2.31 2.66 1.55 1.31 1.24 3.35 2.04 0.68 1.55 1.27 2.17 2.09

0.36 0.42 0.33 0.42 0.41 0.52 0.44 2.32 1.92 2.15 1.35 0.68 0.73 0.63 1.01 2.00 1.06 1.86 1.05 1.89 0.85 0.46 0.69 0.79 0.50 1.78 0.42 0.83 1.62 0.61 2.69 1.84

0.45 0.48 0.36 0.49 0.49 0.63 0.50 2.84 2.35 2.62 1.54 0.80 0.87 0.75 1.21 2.43 1.29 2.23 1.26 2.44 1.02 0.53 0.84 0.91 0.56 2.13 0.47 1.00 1.91 0.71 3.43 2.24

Appendix 2 Colorimetric values of the solid-colour yarn dyed fabrics measured by the spectrophotometer Datacolor 650 and the single yarns measured by ICM under CIE standard illuminant D65 in the colour matching experiment

Solid-colour yarn dyed fabrics Standard samples L* 1 2 3 4 5 6 7 8 9 10 11 12

77.02 30.87 19.09 16.53 32.88 48.78 16.96 18.75 33.53 63.95 20.75 31.06

a* 4.70 29.16 1.09 0.53 0.62 9.96 0.36 1.64 45.80 5.70 13.20 38.06

Single yarns Batch samples

b*

L*

20.01 25.90 6.07 0.69 6.56 30.16 1.77 6.43 19.67 22.78 6.83 13.21

77.19 30.77 19.44 16.33 32.52 47.78 17.46 18.99 33.40 63.24 20.45 30.01

a* 4.89 29.04 0.95 0.50 0.60 9.91 0.27 1.24 46.10 5.67 12.46 38.30

Standard samples b*

L*

19.14 26.06 6.07 0.67 6.81 30.56 1.84 5.21 20.06 23.45 6.39 13.68

72.25 30.88 21.76 17.42 36.29 47.09 18.24 22.04 31.27 63.59 24.00 27.46

a* 3.88 29.21 1.08 0.29 1.12 8.91 0.09 1.62 45.64 5.18 15.40 35.78

Batch samples b*

L*

11.66 26.15 7.84 2.01 6.24 27.88 2.87 7.76 19.92 16.55 8.28 12.55

72.10 30.63 21.95 17.80 35.44 45.75 19.00 21.46 31.32 64.03 23.60 26.55

a* 4.03 28.94 0.72 0.03 1.26 8.99 0.23 1.19 44.52 5.05 14.68 34.86

b* 11.15 26.37 7.99 2.57 6.41 28.82 3.21 6.83 19.28 15.76 7.97 11.69 Continued

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Appendix 2 (Continued) Solid-colour yarn dyed fabrics Standard samples

13 14 15 16 17 18 19 20 21 22 23 24

Single yarns Batch samples

Standard samples

Batch samples

L*

a*

b*

L*

a*

b*

L*

a*

b*

L*

a*

b*

21.32 18.62 33.36 50.33 31.20 50.74 75.74 37.72 31.18 28.09 52.04 77.10

0.03 1.25 2.34 0.58 3.31 0.68 4.87 48.09 11.90 37.10 4.64 5.94

0.40 12.56 14.62 2.94 32.62 2.94 17.67 3.06 0.62 1.57 32.74 19.16

21.69 18.37 33.14 50.67 30.82 50.33 75.62 37.52 31.36 27.85 50.89 75.85

0.08 1.10 2.02 0.59 3.25 0.49 4.57 47.87 11.83 35.21 3.83 4.70

0.44 12.48 14.55 2.96 32.34 2.97 17.28 3.15 0.55 0.00 36.26 17.82

14.20 16.61 37.70 54.21 29.62 54.48 72.76 34.99 29.63 26.28 49.16 73.12

0.71 1.89 2.68 0.71 3.17 0.72 3.53 46.53 12.28 38.09 4.94 4.37

0.19 13.28 13.66 2.69 32.10 2.77 10.71 0.99 0.58 1.08 33.52 11.34

14.92 16.77 37.73 53.63 28.81 52.67 72.36 33.79 28.73 25.91 49.70 72.66

0.61 1.42 2.86 0.59 3.15 0.41 3.61 45.34 12.31 37.56 5.24 3.77

0.21 13.40 13.78 2.65 31.72 2.71 10.83 1.11 0.45 1.06 33.87 10.76

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