Journal of Textile Research ›› 2022, Vol. 43 ›› Issue (11): 119-126.doi: 10.13475/j.fzxb.20210903408

• Dyeing and Finishing & Chemicals • Previous Articles     Next Articles

Whiteness formulae evaluation of non-fluorescent fabrics by psychophysical experiments

YANG Hongying1(), QI Mengyuan1,2, YANG Zhihui1, YANG Yanli1, ZHANG Jingjing1, XIE Wanzi3   

  1. 1. College of Textile, Zhongyuan University of Technology, Zhengzhou, Henan 450007, China
    2. College of Textile & Clothing, Qingdao University, Qingdao, Shandong 266100, China
    3. College of Textile Science and Engineering, Jiangnan University, Wuxi, Jiangsu 214122, China
  • Received:2021-09-10 Revised:2022-08-26 Online:2022-11-15 Published:2022-12-26

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Abstract:

In order to choose the whiteness formula that is closest to human perception for non-fluorescent textile whiteness evaluation, 9 whiteness formulae were studied. White samples were selected from self-made non-fluorescent fabrics using white discrimination visual evaluation, and then 28 and 85 samples were selected to carry out 2 psychophysical experiments of pairwise comparison method and category determination method respectively. More than 10,000 visual evaluation data were processed for comparing and evaluating the predictive performance of the 9 whiteness formulae. Results show that when the whiteness formulae were evaluated by the pairwise comparison method and the category judgment method, Hunter2 formula performed the best for both cases. Therefore, for the non-fluorescent fabrics in this study, the Hunter2 whiteness formula originally designed for evaluating fluorescent fabrics is in the best agreement with the visual perception of human eyes.

Key words: non-fluorescent fabric, whiteness formula, visual evaluation, pairwise comparison method, category determination method

CLC Number: 

  • TS197

Fig.1

Dyeing process curve"

Fig.2

Distribution of white samples for psychophysics experiments in chromaticity diagram"

Tab.1

Description of 9-level scale in category determination method"

类别得分 英文描述 中文定义
1 least imaginable 最小程度的
2 very little mildly 很微小程度的
3 mildly 较小程度的
4 moderately 一般的
5 medially 中等的
6 moderately highly 一定程度的
7 mildly highly 较大程度的
8 very highly 很大程度的
9 highest imaginable 最大程度的

Tab.2

Observer precision in pairwise comparison experiments"

指标 误判率WD/%
最大值 最小值 平均值
准确度 10 7 8
重复性 11 5 7

Tab.3

Frequency matrix from pairwise comparison visual experiments"

编号 1 2 3 4 5 6 … 28
1 8 0 0 0 10 … 0
2 16 0 0 0 8 … 0
3 24 24 0 16 24 … 0
? ? ? ? ? ? ? ? ?
28 24 24 24 0 24 24 … 0

Tab.4

z-score matrix in ascending order obtained from pairwise comparison visual experiment"

编号 26 25 4 24 14 … 1
1 -2.47 -2.47 -2.47 -2.47 -2.47 … 0
2 -2.47 -2.47 -2.47 -2.47 -2.47 … 0.43
3 -2.47 -2.47 -2.47 -2.47 -2.47 … 2.47
? ? ? ? ? ? ? ?
28 -2.47 -2.47 -2.47 -2.47 -2.47 … 2.47
平均值 -2.24 -1.93 -1.69 -1.64 -1.55 … 2.12
等级 1 2 3 4 5 … 28

Tab.5

Visual whiteness differences between each color sample and No.26 sample from pairwise comparison experiment"

编号 d(1-26) d(2-26) d(3-26) d(4-26) … d(28-26)
Δvi-Δv26 4.36 4.30 2.99 0.55 … 1.86

Fig.3

Visual whiteness difference ΔV of 28 non-fluorescent samples"

Tab.6

Visual whiteness difference of samples by category judgment method"

编号 1 2 3 4 5 … 85
白度值 8.82 2.25 22.43 -15.36 38.70 … 35.33

Tab.7

Predictive performance of whiteness formulas from Paired comparison method"

公式 r WD/% ρ STRESS 总排序
WHunter1 0.313(8) 39.7(7) 0.272(8) 74.83(8) 31(8)
WHunter2 0.93(1) 10.9(1) 0.922(1) 18.96(1) 4(1)
WGanz 0.868(5) 14.6(3) 0.864(4) 26.12(4) 16(4)
WGrum 0.912(2) 14.6(3) 0.880(3) 21.56(2) 10(2)
WCIE10 0.91(3) 12.4(2) 0.904(2) 21.58(3) 10(2)
WUchida 0.881(4) 16.4(4) 0.862(5) 28.71(5) 18(5)
WC/V -0.015(9) 57.9(8) -0.242(9) 94.64(9) 35(9)
WUV 0.721(6) 23.8(6) 0.729(7) 59.96(6) 25(6)
WLAB 0.684(7) 23.3(5) 0.73(6) 66.06(7) 25(6)

Tab.8

Comparison of Predictive performance of whiteness formulas from pairwise comparison method (F-test)"

白度公式 WHunter1 WHunter2 WGanz WGrum WCIE10 WUchida WC/V WUV WLAB
WHunter1 0.06* 0.12* 0.08* 0.08* 0.15* 1.6 0.64 0.78
WHunter2 15.58* 1.9 1.29 1.3 2.29* 24.92* 10.00* 12.14*
WGanz 8.21* 0.53 0.68 0.68 1.21 13.13* 5.27* 6.40*
WGrum 12.05* 0.77 1.47 1 1.77 19.27* 7.73 9.39*
WCIE10 12.02* 0.77 1.47 1 1.77 19.23* 7.72 9.37*
WUchida 6.79* 0.44* 0.83 0.56 0.56 10.87* 4.36* 5.29*
WC/V 0.63 0.04* 0.08* 0.05* 0.05* 0.09* 0.40* 0.49*
Wuv 1.56 0.10* 0.19* 0.13* 0.13* 0.23* 2.49* 1.21
WLAB 1.28 0.08* 0.16* 0.11* 0.11* 0.19* 2.05* 0.82

Tab.9

Predictive performance of whiteness formula by category judgment method"

指标 WHunter1 WHunter2 WGanz WGrum WCIE10 WUchida WC/V WUV WLAB
r 0.419(8) 0.949(1) 0.914(4) 0.921(3) 0.943(2) 0.848(5) 0.028(9) 0.587(6) 0.562(7)
ρ 0.379(8) 0.951(1) 0.921(3) 0.868(4) 0.941(2) 0.857(5) -0.064(9) 0.657(7) 0.674(6)
总排序 16(8) 2(1) 7(3) 7(3) 4(2) 10(5) 18(9) 13(6) 13(6)

Fig.4

Comparison of visual whiteness difference ΔV and calculated whiteness difference ΔW of 28 samples by pairwise comparison method"

Fig.5

Comparison of visual whiteness difference ΔV and calculated whiteness difference ΔW of 85 samples by category judgment method"

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