Journal of Textile Research ›› 2019, Vol. 40 ›› Issue (11): 45-49.doi: 10.13475/j.fzxb.20181100806

• Textile Engineering • Previous Articles     Next Articles

Local fabric texture stability characterization using general dictionary

WU Ying1,2(), ZHAN Zhu3, WANG Jun3,4   

  1. 1. School of Fashion Design & Engineering, Zhejiang Sci-Tech University, Hangzhou, Zhejiang 310018, China
    2. Zhejiang Province Engineering Laboratory of Clothing Digital Technology, Zhejiang Sci-Tech University, Hangzhou, Zhejiang 310018, China
    3. College of Textiles, Donghua University, Shanghai 201620, China
    4. Key Laboratory of Textile Science & Technology, Ministry of Education, Donghua University, Shanghai 201620, China
  • Received:2018-11-02 Revised:2019-03-07 Online:2019-11-15 Published:2019-11-26

Abstract:

In order to improve the effect of fixed dictionary on fabric texture, a method for characterizing fabric texture based on general dictionary was proposed. Firstly, the dictionary learning method was preferred. Secondly, eight kinds of arbitrary normal fabric samples and 20 samples with different weave patterns were selected respectively, and then a general dictionary, a general dictionary of four organizational structures and a general dictionary of joint organizational structure were obtained by the preferred dictionary learning method. Finally, the validity of the general dictionary was verified by experiments. The results show that the common general dictionary can adapt to the fabric texture better than the fixed dictionary. On this basis, the performance of three general dictionaries was compared. The test results show that compared with fixed dictionaries, general dictionaries can better characterize fabric texture under the same experiment conditions; and different types of general dictionaries can have better universality or specificity.

Key words: fabric texture, dictionary learning, general dictionary, fabric weave pattern

CLC Number: 

  • TS101.9

Fig.1

Process of general dictionary to represent fabric texture"

Fig.2

Learned dictionary. (a) MOD dictionary;(b) K-SVD dictionary"

Tab.1

Comparable results for two algorithms"

学习算法 编号 PSNR/dB SSIM 时间/s
K-SVD字典
学习法
1# 44.40 0.96 566.50
2# 30.80 0.93 563.14
MOD字典
学习法
1# 43.40 0.95 549.32
2# 30.57 0.93 538.65

Fig.3

Fabric original sample images"

Fig.4

General dictionary. (a) K-SVD general dictionary; (b) MOD general dictionary"

Tab.2

Quantitative test results for two general dictionaries"

字典 编号 PSNR/dB SSIM 时间/s
基于MOD算法
的通用字典
1# 39.98 0.88 89.31
2# 27.71 0.71 89.12
基于K-SVD算法
的通用字典
1# 41.53 0.92 89.36
2# 30.53 0.86 89.08

Fig.5

2# sample's reconstructed images with different sparse cardinality T values"

Fig.6

Fabric texture representation result with different sparse cardinality. (a) PSNR; (b) SSIM; (c) Time"

Fig.7

Comparative test for two kinds of general dictionaries"

Fig.8

Fabric sample images"

Tab.3

Comparative test results for different general dictionaries"

通用
字典
PSNR/dB SSIM
2# 3# 4# 5# 2# 3# 4# 5#
组织结构 34.93 35.03 30.82 26.66 0.95 0.99 0.96 0.91
联合组
织结构
34.94 34.53 30.40 26.48 0.95 0.98 0.95 0.91
普通 33.27 32.36 29.50 26.10 0.93 0.97 0.94 0.91
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