Journal of Textile Research ›› 2019, Vol. 40 ›› Issue (05): 163-169.doi: 10.13475/j.fzxb.20180407007

• Management & Information • Previous Articles     Next Articles

Color shading detection and rating system for denim based on computer vision

HUANG Jiajun, KE Wei, WANG Jing, DENG Zhongmin()   

  1. Key Laboratory of Textile Fiber Products, Ministry of Education, Wuhan Textile University,Wuhan, Hubei 430073, China
  • Received:2018-04-27 Revised:2019-01-25 Online:2019-05-15 Published:2019-05-21
  • Contact: DENG Zhongmin E-mail:dzm@wtu.edu.cn

RichHTML

11

PDF (PC)

123

Abstract:

Focusing on subjective difference based on the human eye evaluation of current denim color detection,a computer vision-based denim color shading detection and rating system was proposed. Firstly, images of denim washing cloths and standard cloths under a standard light source were collected using a camera. Secondly, computer graphics principles and techniques, image processing, color space conversion and other technologies were adopted. Finally,a color shading detection and rating system for denim clothing was established by using MatLab and VC++ mixed programming technology. In order to acquire more accurate ratings data, a concept of percentage of diversity factor-value of chromatism was proposed, and the color shading diversity factor equation was obtained by fitting the value of chromatism under different degrees of difference to be as a rating indicator of denim clothing color shading detection system. The experimental results indicate that the color shading detection and grading system for denim based on computer vision has good consistency with the visual evaluation method, and the data value obtained by the system is more objective and accurate.

Key words: color shading detection, color space conversion, color shading calculate, rating system, image processing

CLC Number: 

  • TS187

Fig.1

Denim clothing color detection system working chart"

Fig.2

Denim clothing RGB image (a) and brightness image (b)"

Fig.3

Comparison of denim clothing. (a) 3 pixel×3 pixel median filter; (b) 3 pixel×3 pixel mean filter"

Fig.4

Re-synthesized RGB image"

Tab.1

Results of color difference and diversity factor"

色差值 差异度/%
0.285 8 0
0.785 1 5
1.368 7 10
1.924 6 15
5.823 7 40
59.011 2 100

Fig.5

Fitting curve of diversity factor-value of chromatism. (a)Quadratic curve; (b)Cubic curve; (c)Rational function"

Tab.2

Fitting equations for diversity factor-value of chromatism"

曲线拟合 拟合方程 误差平方和 R2
二次曲线拟合 y=0%,x≤0.2858y=(0.1017x2+7.709x-0.8893)×100%,x>0.2858 4.347 00 0.999 4
三次曲线拟合 y=0%,x≤0.2858y=(0.00656x3-0.5309x2+10.23x-2.841)×100%,x>0.2858, 0.580 5 0.999 8
有理函数拟合 y=0%,x≤0.2858y=(118.7x-37.27x+10.64)×100%,x>0.2858 0.409 5 0.999 9

Fig.6

Denim clothing color difference detection rating system interface"

Tab.3

Denim clothing color detection rating results compared with expert visual inspection results"

牛仔布
样本		 色差值
(CIEDE2000)		 差异
度/%		 目测评级结果
专家1 专家2
第1组 0.352 8 0.42 4~5级 4~5级
第2组 0.588 8 2.91 4级 4级
第3组 0.721 8 4.26 4级 4级
第4组 0.861 7 5.65 4级 3~4级
第5组 1.285 8 9.67 3~4级 4级
第6组 1.741 5 13.69 3~4级 3~4级
第7组 1.889 6 14.93 3~4级 3~4级
第8组 2.113 4 16.75 不合格 不合格
第9组 5.077 3 35.96 不合格 不合格
第10组 7.651 4 47.26 不合格 不合格
[1] 孙飞, 张胜文, 方喜峰, 等. 纺织品色牢度计算机辅助测试系统的研制[J]. 自动化与仪表, 2007,22(2):70-73.
SUN Fei, ZHANG Shengwen, FANG Xiwen, et al. Research on computer aided test textile color degree[J]. Automation & Instrumentation, 2007,22(2):70-73.
[2] 韩小贺, 成刚虎, 向志爱. 色空间转换在印刷品质量检测中的应用研究[J]. 包装工程, 2009(1):101-102.
HAN Xiaohe, CHENG Ganghu, XIANG Zhiai. Study on application of color space conversion in printing quality inspection.[J] Packaging Engineering, 2009(1):101-102.
[3] 郑成辉. 图像法评价织物变色牢度等级探讨[J] . 轻纺工业与技术, 2010,39(6):26-28.
ZHENG Chenghui. Explore the grade evaluation of color fastness with image analysis[J]. Light and Textile Industry and Technology, 2010,39(6):26-28.
[4] 王丽华. DigiEye数码测色系统在纺织品色牢度评级中的应用[J]. 染整技术, 2017(9):58-60,64.
WANG Lihua. Application of DigiEye digital color measuring system in textiles color fastness evalua-tion[J].Textile Dyeing and Finishing Journal, 2017(9):58-60,64.
[5] 丁建华, 娄德波, 宋国玺, 等. 彩色地质图图像的交互式矢量化方法及其系统: 101853514 B[P]. 2010-10-08.
DING Jianhua, LOU Debo, SONG Guoxi, et al. Interactive vectorization method and system of color geological image: 101853514 B[P].2010-10-08.
[6] 张小燕, 程韦. 快速色差评价[J]. 湖南工业大学学报, 2011,25(2):77-80.
ZHANG Xiaoyan, CHENG Wei. Fast color shading evaluation[J]. Journal of Hunan University of Technology, 2011,25(2):77-80.
[7] 张庆红, 刘建立, 高卫东. 基于图像处理的织物耐洗涤色牢度等级评定[J]. 纺织学报, 2013,34(11):100-102.
ZHANG Qinghong, LIU Jianli, GAO Weidong. Grade evaluation of color fastness to laundering based on image analysis[J]. Journal of Textile Research, 2013,34(11):100-102.
[8] 钱荣盛, 姚克明. 一种纺织品的色差检测方法研究[J]. 现代商贸工业, 2018(1):191-192.
QIAN Rongsheng, YAO Keming. Study on a color shading detection method for textiles[J].Modern Business Trade Industry, 2018(1):191-192.
[9] 冉友廷, 邓中民. 基于计算机视觉的纺织品色牢度检测方法[J]. 针织工业, 2012(8):65-68.
RAN Youting, DENG Zhongmin. Research about fabric color fastness detection based on computer vision[J]. Knitting Industries, 2012(8):65-68.
[10] 丁若垚, 雷建萍, 张永立, 等. GB 31701标准的实施对牛仔面料耐湿摩擦色牢度的影响[J]. 中国纤检, 2016(3):104-107.
DING Ruoyao, LEI Jianping, ZHANG Yongli et al.GB 31701 and its affect on wet rubbing color fastness in jeanswear[J]. China Fiber Inspection, 2016(3):104-107.
[11] 石美红, 申亮, 龙世忠, 等. 从RGB到HSI色彩空间转换公式的修正[J].纺织高校基础科学学报, 2008(3):351-355.
SHI Meihong, SHEN Liang, LONG Shizhong, et al. The revision of conversion formula from RGB color space to HSI color space[J]. Basic Sciences Journal of Textile Universities, 2008(3):351-355.
[12] SHARMA G, WU Wencheng, EDUL N Dalal. The CIEDE2000. Color-difference formula: implementation notes, supplementary test data, and mathematical observations[J]. ECE Department and Department of Biostatistics and Computational Biology, 2005,30:21-29.
[13] 马艳, 宁铎, 杨杰. 基于色差-灰度差模型的色牢度定级方法研究[J]. 西部皮革, 2017(5):29-33.
MA Yan, NING Duo, YANG Jie. Research on color fastness grading based on chrominance-gray difference model[J].West Leather, 2017(5):29-33.
[1] ZHANG Zhengye, XIN Binjie, DENG Na, CHEN Yang, XING Wenyu. Research and application of algorithm for measuring hemp fiber cross-sectional parameters based on boundary tracking [J]. Journal of Textile Research, 2020, 41(02): 39-43.
[2] WU Yilun, LI Zhongjian, PAN Ruru, GAO Weidong, ZHANG Ning. Weft knitted fabric appearance simulation using colored spun yarn image [J]. Journal of Textile Research, 2019, 40(06): 111-116.
[3] WANG Wendi, XIN Binjie, DENG Na, LI Jiaping, LIU Ningjuan. Identification and application of yarn hairiness using adaptive threshold method under single vision [J]. Journal of Textile Research, 2019, 40(05): 150-156.
[4] CAI Yichao, ZHOU Xiao, SONG Mingfeng, MOU Xin'gang. Defect detection of cheese yarn based on multi-scale multi-direction template convolution [J]. Journal of Textile Research, 2019, 40(04): 152-157.
[5] . Detection and evaluation on yarn hairiness of blackboard with image processing [J]. JOURNAL OF TEXTILE RESEARCH, 2018, 39(08): 144-149.
[6] . Position recognition of spinning yarn breakage based on convolution neural network [J]. JOURNAL OF TEXTILE RESEARCH, 2018, 39(06): 136-141.
[7] . Detecting method of foreign fibers in seed cotton based on deep-learning [J]. JOURNAL OF TEXTILE RESEARCH, 2018, 39(06): 131-135.
[8] . Spinning breakage detection based on optimized hough transform [J]. JOURNAL OF TEXTILE RESEARCH, 2018, 39(04): 36-41.
[9] . Application of algorithm with improved frequency-tuned salient region [J]. JOURNAL OF TEXTILE RESEARCH, 2018, 39(03): 154-160.
[10] . On-line yarn cone defects detection system based on machine vision [J]. JOURNAL OF TEXTILE RESEARCH, 2018, 39(01): 139-145.
[11] . Rapid identification method of cashmere and wool based on bag-of-visual-word [J]. JOURNAL OF TEXTILE RESEARCH, 2017, 38(07): 130-134.
[12] . Simulation of realistic yarn-dyed fabric using colored spun yarn images [J]. JOURNAL OF TEXTILE RESEARCH, 2017, 38(05): 37-42.
[13] . Detecting method of foreign fibers in seed cotton using double illumination imaging [J]. JOURNAL OF TEXTILE RESEARCH, 2017, 38(04): 32-38.
[14] . Measurement for fabric wrinkle resistance by simulating actual wear [J]. JOURNAL OF TEXTILE RESEARCH, 2017, 38(03): 56-60.
[15] . Detection of fabric defects based on Gabor filters and Isomap [J]. JOURNAL OF TEXTILE RESEARCH, 2017, 38(03): 162-167.
Viewed
Full text


Abstract

Cited
  Shared   
  Discussed   
No Suggested Reading articles found!
京ICP备14006648号
Copyright 2021 © Editorial office of Journal of Textile Research
Supported by Beijing Magtech Co.Ltd