Journal of Textile Research ›› 2022, Vol. 43 ›› Issue (10): 38-44.doi: 10.13475/j.fzxb.20210904207

• Textile Engineering • Previous Articles     Next Articles

Optimization of full spectrum color matching algorithm for color spun yarn based on visual characteristics

CHENG Lu1, MA Chongqi2, ZHOU Huimin1, WANG Ying1, XIA Xin1()   

  1. 1. Xinjiang University, Urumqi, Xinjiang 830046, China
    2. School of Textile Science and Engineering, Tiangong University, Tianjin 300387, China
  • Received:2021-09-13 Revised:2022-04-04 Online:2022-10-15 Published:2022-10-28
  • Contact: XIA Xin E-mail:xjxiaxin@163.com

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Abstract:

In order to improve the accuracy and applicability of computer color matching algorithm for color spunyarns, a full-spectrum color matching algorithm was proposed based on the classical Stearns Noechel optical theoretical model, aiming at the problems that it is difficult to minimize error in calculated color difference value and that in matching relative deviation. The sensitivity coefficient of human visual characteristics to reflected light at different wavelengths was determined by exploring human visual characteristics, and it was introduced into the color matching algorithm for weighted calculation to predict the monochrome fiber mixing ratio. The color matching effect was evaluated by predicting the color difference value, the relative deviation value of the ratio and the Euclidean distance. Results show that the color matching algorith with Poisson distribution introduced to the human eye sensitivity coefficient is optimal, with the average prediction color difference value being 0.29 and all within 1, the ratio of the average relative deviation value being minimal 0.612, Euclidean distance average being 0.087 which is relatively small. When using the improved color matching algorithm, the prediction of the color difference value can be achieved through one calculation, leading to a small color difference with higher accuracy. With the improved algorithm, computer assisted color matching for color spunyarns can be primarily achieved.

Key words: color spun yarn, full spectrum color matching, visual characteristic, color difference, relative deviation in color matching, computer color matching algorithm

CLC Number: 

  • TS104.5

Fig.1

Reflectance curve of monochromatic sample"

Tab.1

Number and quality ratio of mixed standard color sample"

试样
编号		 纤维
质量比		 试样
编号		 纤维
质量比		 试样
编号		 纤维
质量比
1# 0.1∶0.8∶0.1 19# 0.3∶0.5∶0.2 37# 0.1∶0.7∶0.2
2# 0.1∶0.7∶0.2 20# 0.3∶0.3∶0.4 38# 0.1∶0.1∶0.8
3# 0.1∶0.6∶0.3 21# 0.3∶0.2∶0.5 39# 0.2∶0.7∶0.1
4# 0.1∶0.5∶0.4 22# 0.3∶0.1∶0.6 40# 0.2∶0.6∶0.2
5# 0.1∶0.4∶0.5 23# 0.4∶0.5∶0.1 41# 0.2∶0.5∶0.3
6# 0.1∶0.3∶0.6 24# 0.4∶0.4∶0.2 42# 0.3∶0.6∶0.1
7# 0.1∶0.2∶0.7 25# 0.4∶0.3∶0.3 43# 0.3∶0.5∶0.2
8# 0.1∶0.1∶0.8 26# 0.4∶0.2∶0.4 44# 0.3∶0.4∶0.3
9# 0.2∶0.7∶0.1 27# 0.4∶0.1∶0.5 45# 0.4∶0.5∶0.1
10# 0.2∶0.6∶0.2 28# 0.5∶0.4∶0.1 46# 0.4∶0.4∶0.2
11# 0.2∶0.5∶0.3 29# 0.5∶0.3∶0.2 47# 0.4∶0.3∶0.3
12# 0.2∶0.4∶0.4 30# 0.5∶0.2∶0.3 48# 0.5∶0.4∶0.1
13# 0.2∶0.3∶0.5 31# 0.5∶0.1∶0.4 49# 0.5∶0.3∶0.2
14# 0.2∶0.2∶0.6 32# 0.6∶0.3∶0.1 50# 0.6∶0.3∶0.1
15# 0.2∶0.1∶0.7 33# 0.6∶0.2∶0.2 51# 0.6∶0.2∶0.2
16# 0.3∶0.6∶0.1 34# 0.6∶0.1∶0.3 52# 0.7∶0.2∶0.1
17# 0.1∶0.8∶0.1 35# 0.7∶0.2∶0.1 53# 0.7∶0.1∶0.2
18# 0.1∶0.7∶0.2 36# 0.1∶0.8∶0.1 54# 0.8∶0.1∶0.1

Fig.2

Chromatic diagram of sample"

Tab.2

Calculation results of initial fitting which were not improved"

样品编号 预测配比 色差 配比偏差 欧式距离 样品编号 预测配比 色差 配比偏差 欧式距离
1# 0.08∶0.73∶0.19 0.20 1.21 0.11 28# 0.45∶0.28∶0.27 0.40 0.60 0.10
2# 0.05∶0.70∶0.24 0.15 0.71 0.07 29# 0.51∶0.16∶0.33 0.46 0.80 0.09
3# 0.05∶0.63∶0.32 0.16 0.61 0.06 30# 0.51∶0.35∶0.14 0.40 0.70 0.11
4# 0.05∶0.57∶0.37 0.04 0.68 0.09 31# 0.53∶0.26∶0.21 0.47 0.49 0.10
5# 0.06∶0.50∶0.44 0.11 0.75 0.12 32# 0.58∶0.16∶0.25 0.51 0.82 0.08
6# 0.07∶0.37∶0.56 0.04 0.61 0.09 33# 0.62∶0.25∶0.13 0.51 0.65 0.10
7# 0.09∶0.30∶0.61 0.28 0.70 0.13 34# 0.66∶0.17∶0.17 0.52 0.93 0.09
8# 0.15∶0.23∶0.62 0.62 2.00 0.23 35# 0.72∶0.17∶0.11 0.53 0.86 0.10
9# 0.18∶0.62∶0.20 0.05 1.21 0.13 36# 0.10∶0.79∶0.11 1.28 0.14 0.02
10# 0.16∶0.53∶0.31 0.06 0.90 0.14 37# 0.14∶0.70∶0.15 1.91 0.68 0.06
11# 0.15∶0.50∶0.36 0.03 0.46 0.08 38# 0.08∶0.15∶0.77 0.53 0.70 0.06
12# 0.15∶0.46∶0.39 0.13 0.40 0.07 39# 0.17∶0.72∶0.12 0.59 0.35 0.04
13# 0.16∶0.36∶0.48 0.27 0.42 0.07 40# 0.22∶0.62∶0.15 1.57 0.40 0.06
14# 0.20∶0.30∶0.50 0.45 0.70 0.14 41# 0.23∶0.54∶0.23 1.63 0.49 0.09
15# 0.25∶0.19∶0.56 0.49 1.38 0.18 42# 0.29∶0.61∶0.10 0.87 0.08 0.02
16# 0.25∶0.59∶0.16 0.15 0.79 0.08 43# 0.28∶0.52∶0.20 0.78 0.13 0.03
17# 0.25∶0.46∶0.29 0.20 0.71 0.11 44# 0.26∶0.45∶0.29 0.86 0.31 0.07
18# 0.25∶0.31∶0.44 0.26 0.32 0.07 45# 0.35∶0.53∶0.12 0.37 0.37 0.06
19# 0.27∶0.23∶0.51 0.31 0.27 0.05 46# 0.39∶0.43∶0.17 0.76 0.24 0.04
20# 0.31∶0.15∶0.54 0.31 0.63 0.08 47# 0.46∶0.34∶0.20 1.17 0.59 0.12
21# 0.35∶0.46∶0.18 0.29 1.02 0.10 48# 0.47∶0.44∶0.09 0.41 0.23 0.05
22# 0.33∶0.44∶0.24 0.29 0.46 0.09 49# 0.51∶0.33∶0.16 0.66 0.32 0.05
23# 0.34∶0.35∶0.31 0.32 0.36 0.08 50# 0.60∶0.33∶0.07 0.37 0.45 0.05
24# 0.37∶0.27∶0.36 0.35 0.52 0.08 51# 0.61∶0.21∶0.18 0.50 0.17 0.02
25# 0.42∶0.16∶0.42 0.40 0.79 0.10 52# 0.76∶0.20∶0.04 0.51 0.67 0.08
26# 0.43∶0.40∶0.16 0.39 0.77 0.09 53# 0.72∶0.13∶0.15 0.34 0.58 0.06
27# 0.42∶0.35∶0.22 0.39 0.44 0.10 54# 0.80∶0.12∶0.08 0.53 0.49 0.03

Tab.3

Calculation result of initial prediction is optimized for first time (Normal distribution)"

样品编号 预测配比 色差 配比偏差 欧式距离 样品编号 预测配比 色差 配比偏差 欧式距离
1# 0.07∶0.76∶0.16 0.26 0.97 0.08 28# 0.46∶0.26∶0.28 0.04 0.41 0.07
2# 0.05∶0.72∶0.23 0.23 0.68 0.06 29# 0.34∶0.06∶0.60 0.18 1.18 0.26
3# 0.05∶0.63∶0.32 0.22 0.61 0.06 30# 0.53∶0.32∶0.15 0.21 0.66 0.09
4# 0.05∶0.57∶0.37 0.05 0.68 0.09 31# 0.54∶0.25∶0.21 0.30 0.41 0.08
5# 0.06∶0.52∶0.42 0.11 0.83 0.15 32# 0.59∶0.16∶0.25 0.13 0.73 0.07
6# 0.07∶0.40∶0.53 0.06 0.71 0.12 33# 0.49∶0.06∶0.46 0.18 4.58 0.44
7# 0.09∶0.29∶0.62 0.33 0.66 0.13 34# 0.52∶0.06∶0.42 0.06 1.75 0.29
8# 0.15∶0.22∶0.63 0.68 1.91 0.21 35# 0.62∶0.05∶0.32 0.26 2.95 0.29
9# 0.17∶0.64∶0.19 0.04 1.07 0.11 36# 0.11∶0.82∶0.07 0.72 0.47 0.04
10# 0.15∶0.55∶0.29 0.12 0.78 0.11 37# 0.15∶0.73∶0.12 1.17 1.00 0.10
11# 0.15∶0.50∶0.35 0.03 0.44 0.07 38# 0.08∶0.13∶0.79 0.16 0.56 0.04
12# 0.15∶0.49∶0.35 0.06 0.59 0.12 39# 0.17∶0.74∶0.10 0.32 0.25 0.05
13# 0.17∶0.41∶0.42 0.21 0.67 0.14 40# 0.23∶0.65∶0.11 0.96 0.68 0.11
14# 0.20∶0.32∶0.48 0.48 0.79 0.17 41# 0.25∶0.57∶0.18 0.87 0.76 0.15
15# 0.26∶0.19∶0.55 0.51 1.43 0.19 42# 0.29∶0.63∶0.08 0.66 0.24 0.03
16# 0.26∶0.58∶0.17 0.14 0.83 0.08 43# 0.29∶0.55∶0.15 0.09 0.36 0.07
17# 0.24∶0.50∶0.26 0.20 0.51 0.08 44# 0.28∶0.49∶0.23 0.22 0.53 0.11
18# 0.26∶0.34∶0.40 0.21 0.29 0.06 45# 0.36∶0.55∶0.10 0.02 0.25 0.07
19# 0.28∶0.25∶0.47 0.18 0.36 0.06 46# 0.41∶0.46∶0.13 0.05 0.53 0.09
20# 0.32∶0.16∶0.52 0.11 0.76 0.10 47# 0.47∶0.36∶0.18 0.70 0.78 0.15
21# 0.35∶0.47∶0.18 0.34 0.95 0.10 48# 0.48∶0.45∶0.07 0.16 0.48 0.06
22# 0.33∶0.43∶0.24 0.15 0.43 0.08 49# 0.55∶0.34∶0.11 0.30 0.65 0.11
23# 0.35∶0.35∶0.31 0.12 0.32 0.07 50# 0.61∶0.33∶0.05 0.35 0.61 0.06
24# 0.37∶0.25∶0.37 0.01 0.41 0.07 51# 0.61∶0.22∶0.17 0.47 0.22 0.03
25# 0.29∶0.07∶0.64 0.24 0.85 0.18 52# 0.76∶0.20∶0.04 0.87 0.69 0.08
26# 0.45∶0.39∶0.17 0.36 0.80 0.09 53# 0.72∶0.13∶0.15 0.34 0.59 0.06
27# 0.43∶0.34∶0.23 0.21 0.40 0.08 54# 0.80∶0.13∶0.08 0.54 0.49 0.03

Tab.4

Second optimization predicted the results of initial calculation (Poisson distribution)"

样品编号 预测配比 色差 配比偏差 欧式距离 样品编号 预测配比 色差 配比偏差 欧式距离
1# 0.07∶0.75∶0.18 0.08 1.07 0.09 28# 0.45∶0.26∶0.29 0.23 0.42 0.08
2# 0.05∶0.73∶0.22 0.13 0.65 0.06 29# 0.50∶0.15∶0.35 0.24 0.63 0.07
3# 0.05∶0.64∶0.31 0.13 0.60 0.06 30# 0.51∶0.36∶0.13 0.21 0.69 0.12
4# 0.05∶0.58∶0.37 0.02 0.69 0.09 31# 0.52∶0.29∶0.19 0.35 0.62 0.12
5# 0.06∶0.50∶0.44 0.05 0.75 0.13 32# 0.58∶0.16∶0.26 0.31 0.73 0.07
6# 0.07∶0.38∶0.55 0.01 0.64 0.10 33# 0.62∶0.25∶0.13 0.49 0.66 0.10
7# 0.09∶0.29∶0.62 0.19 0.63 0.11 34# 0.65∶0.17∶0.18 0.38 0.92 0.09
8# 0.13∶0.18∶0.69 0.55 1.23 0.14 35# 0.71∶0.20∶0.09 0.51 1.16 0.13
9# 0.18∶0.63∶0.19 0.01 1.12 0.11 36# 0.09∶0.84∶0.07 0.48 0.43 0.05
10# 0.15∶0.55∶0.30 0.05 0.81 0.12 37# 0.12∶0.73∶0.15 0.86 0.54 0.07
11# 0.15∶0.50∶0.36 0.03 0.46 0.08 38# 0.08∶0.16∶0.77 0.35 0.83 0.07
12# 0.15∶0.49∶0.36 0.08 0.57 0.11 39# 0.16∶0.73∶0.11 0.19 0.35 0.05
13# 0.17∶0.39∶0.44 0.08 0.58 0.11 40# 0.21∶0.66∶0.12 0.64 0.55 0.10
14# 0.19∶0.29∶0.51 0.31 0.65 0.13 41# 0.22∶0.56∶0.21 0.85 0.54 0.11
15# 0.24∶0.17∶0.58 0.36 1.12 0.15 42# 0.30∶0.63∶0.07 0.40 0.35 0.04
16# 0.22∶0.65∶0.13 0.04 0.63 0.09 43# 0.27∶0.53∶0.20 0.50 0.16 0.04
17# 0.25∶0.47∶0.29 0.16 0.69 0.11 44# 0.26∶0.46∶0.28 0.64 0.34 0.07
18# 0.25∶0.37∶0.38 0.21 0.42 0.08 45# 0.35∶0.54∶0.12 0.22 0.39 0.07
19# 0.28∶0.25∶0.47 0.21 0.42 0.07 46# 0.40∶0.44∶0.17 0.52 0.26 0.05
20# 0.33∶0.17∶0.50 0.09 1.00 0.13 47# 0.46∶0.34∶0.20 0.69 0.64 0.13
21# 0.35∶0.46∶0.19 0.28 1.05 0.10 48# 0.47∶0.44∶0.09 0.28 0.25 0.05
22# 0.32∶0.45∶0.23 0.17 0.45 0.10 49# 0.52∶0.33∶0.15 0.45 0.35 0.06
23# 0.34∶0.35∶0.31 0.20 0.35 0.08 50# 0.61∶0.33∶0.06 0.26 0.49 0.05
24# 0.36∶0.25∶0.39 0.19 0.38 0.07 51# 0.61∶0.21∶0.18 0.34 0.19 0.03
25# 0.42∶0.15∶0.44 0.18 0.65 0.08 52# 0.76∶0.20∶0.04 0.48 0.68 0.08
26# 0.42∶0.44∶0.14 0.27 0.70 0.10 53# 0.73∶0.13∶0.15 0.22 0.60 0.07
27# 0.43∶0.34∶0.23 0.30 0.44 0.09 54# 0.80∶0.12∶0.07 0.37 0.53 0.04

Fig.3

Comparison of color matching algorithm before and after improvement. (a) Comparison of chromatic aberration; (b) Comparison of ratio relative deviation; (c) Comparison of Euclidean distance"

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