Journal of Textile Research ›› 2022, Vol. 43 ›› Issue (12): 160-166.doi: 10.13475/j.fzxb.20211111307

• Apparel Engineering • Previous Articles     Next Articles

Automatic coloration of clothing pattern based on color parsing of Peking Opera masks

JIA Jing1, CAO Jingwen1, XU Pinghua1,2,3(), LIN Ruibing1, SUN Xiaowan1   

  1. 1. School of Fashion Design & Engineering, Zhejiang Sci-Tech University, Hangzhou, Zhejiang 310018, China
    2. Clothing Engineering Research Center of Zhejiang Province, Hangzhou, Zhejiang 310018, China
    3. Key Laboratory of Silk Culture Heritage and Products Design Digital Technology, Ministry of Culture and Tourism, Hangzhou, Zhejiang 310018, China
  • Received:2021-11-30 Revised:2022-05-23 Online:2022-12-15 Published:2023-01-06
  • Contact: XU Pinghua E-mail:shutexph@163.com

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Abstract:

In order to improve the coloration efficiency of clothing pattern design, an automatic color matching mechanism based on adaptive color clustering of scene images was proposed. 150 images of Peking Opera masks from three roles were collected as the source samples. The Peking Opera mask body of each sample image was obtained by image segmentation and denoising. The bipartite K-means clustering algorithm was utilized to extract adaptively the extracted colors of each sample. In addition, the secondary clustering was carried out to acquire the main color value, proportion and co-occurrence ratio of Peking Opera mask images. A dynamic color matching mechanism integrating the number of color clusters, co-occurrence ration and structure characteristics of the target pattern was designed. Consequently, an automatic color parsing and matching software package was developed. Results confirm that the color matching control parameters, source images, pattern shape and other factors affect the color selection sequence and the final matching effect. The proposed method can quickly achieve the pattern color migration based on the source images, and can provide reference for auxiliary decision-making on clothing pattern color design.

Key words: adaptive clustering, color transfer, Peking Opera facial mask, coloration mechanism, parsing, colthing pattern

CLC Number: 

  • TS941.2

Fig.1

Partial mask images. (a) Sheng role;(b) Jing role;(c) Chou role"

Fig.2

Pre-processing effect of single sample. (a)Graying;(b)Binaryzation;(c)Holes filling;(d)Target extraction;(e)Denoising"

Fig.3

Bipartite K-means clustering"

Fig.4

Color extraction of Chou role masks"

Fig.5

Main color nexus network model of Chou role"

Fig.6

Structure of pattern 1"

Fig.7

Automatic color matching effects of different control parameters. (a)Scheme 1;(b) Scheme 2;(c) Scheme 3;(d) Scheme 4;(e)Scheme 5;(f) Scheme 6"

Fig.8

Automatic coloration effect based on source images of different role. (a) Sheng role;(b) Jing role;(c) Chou role"

Fig.9

Mean square deviation of hue, saturation and brightness in different roles"

Tab.1

Color value and proportion of each role"

角色 输出 主色1 主色2 主色3 主色4 主色5 主色6 主色7 主色8 主色9 主色10
生角 色号 #07020C #4D220C #A77A5F #E7892E #100A11 #D893AE #48322C #722D43 #DD2C2E #715F75
占比/% 21.03 12.45 12.21 10.69 8.90 8.09 7.53 6.82 6.65 5.63
净角 色号 #05030A #3A3142 #8D89B4 #415920 #BC4E59 #E48E2F #C21316 #6A493F #DA9279 #15388D
占比/% 29.32 12.80 9.24 8.78 8.51 8.38 7.98 6.82 4.31 3.86
丑角 色号 #F1DFDA #EB9276 #0A0409 #EFC8CF #251C23 #020006 #6C4A42 #A19AB6 #080808 #8D391A
占比/% 19.96 17.47 16.88 10.76 8.45 8.05 5.82 4.75 3.96 3.90

Fig.10

Automatic color matching effect of symmetric patterns. (a)Pattern 2;(b) Pattern 3;(c) Pattern 4;(d) Pattern 5"

Fig.11

Automatic color matching effect of asymmetric patterns. (a)Pattern 6;(b) Pattern 7;(c) Pattern 8;"

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