Journal of Textile Research ›› 2022, Vol. 43 ›› Issue (05): 97-103.doi: 10.13475/j.fzxb.20210500207

• Textile Engineering • Previous Articles     Next Articles

Lightness prediction method for shaded satin fabrics based on image reconstruction of light and shadow

ZHENG Wenjie1, ZHANG Aidan1,2()   

  1. 1. College of Textile Science and Engineering(International Institute of Silk), Zhejiang Sci-Tech University, Hangzhou, Zhejiang 310018, China
    2. Silk and Fashion Culture Research Center of Zhejiang Province, Zhejiang Sci-Tech University, Hangzhou, Zhejiang 310018, China
  • Received:2021-05-06 Revised:2022-01-25 Online:2022-05-15 Published:2022-05-30
  • Contact: ZHANG Aidan E-mail:zad.andan@163.com

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Abstract:

In order to obtain the brightness value of shaded satin fabrics more accurately, a lightness prediction method based on the shadow reconstruction of fabric image was proposed. The fabric image was separated into three layers: warp and weft graphic layer, shadow layer and texture layer, and the actual color values of the warp and the weft yarn were assigned to the relative area of the three separated image layers when their pixel numbers were counted respectively. After the fabric image brightness value were reconstructed by adding the lightness values, fitting analysis were implemented between the reconstructed one and the actual color measurement data of the fabric. According to the analysis results, the warp and weft area rate, shadow area rate and texture area rate were selected as the independent variables. A regression model for the lightness prediction of the fabric was established based on the three independent variables, and random samples were selected to test the accuracy of the model. The results show that the proximity between the lightness of the warp and weft graphic layer and the measured lightness is 0.15, and the proximity increases from 0.76 to 0.89 when the shadow layer and material layer are added in sequence. The overall relative error of the fabric lightness prediction by the model is within ±4%, the prediction results can be used as references for the design of the fabric with shaded weaves.

Key words: shaded satin weave, image reconstruction, regression analysis, fabric brightness, prediction model

CLC Number: 

  • TS141.9

Fig.1

Diagram of light and shadow reconstruction method of fabric images"

Fig.2

Layered extraction of fabric images and its image illustration. (a)Original digital image; (b)Preprocess window image; (c)Connection area image; (d)Open operational image; (e)White warp image; (f)Black weft image; (g)Shadow image on the white warp; (h)Texture image on black weft"

Fig.3

Diagram of fabric lightness"

Tab.1

One-way analysis of variance for fabric lightness"

试样编号 L1与Lpi L1与Lti L1与Lzi
F值 p值 F值 p值 F值 p值
1* 2.53 0.123 0.06 0.812 0.00 0.948
2* 1.51 0.229 0.27 0.608 0.06 0.815
3* 3.21 0.084 0.03 0.871 0.01 0.917

Tab.2

Results of stepwise regression analysis"

模型编号 R2 调整R2 F值 p值 剔除变量
1# 0.985 0.982 336.008 0 x3、x4
2# 0.961 0.958 343.01 0 x1、x4、x7
3# 0.953 0.950 344.864 0 x1、x3、x4、x7

Tab.3

Results of prediction model validation"

样品
编号		 x1 x2 x3 实测
数据		 预测
数据		 误差
率%
1 2.382 0.299 0.035 50.84 49.82 -2.01
2 2.994 0.409 0.012 65.37 64.59 -0.57
3 2.330 0.219 0.023 52.55 52.08 -0.89
4 2.522 0.377 0.006 68.15 68.80 0.96
5 2.319 0.204 0.039 44.92 44.56 -0.81
6 3.096 0.408 0.006 71.02 69.93 -1.93
7 2.225 0.173 0.009 58.71 59.27 0.96
8 5.834 0.468 0.005 73.91 72.76 -1.55
9 2.255 0.162 0.034 34.97 36.14 3.36
10 2.276 0.256 0.010 60.49 59.86 -1.05
11 2.268 0.260 0.048 38.36 37.59 -2.01
12 2.410 0.210 0.008 63.55 63.20 -0.56
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