Premium
Automatic detection of layout of color yarns of yarn‐dyed fabric. Part 3: Double‐system‐Mélange color fabrics
Author(s) -
Zhang Jie,
Pan Ruru,
Gao Weidong,
Xu Bugao,
Li Wei
Publication year - 2017
Publication title -
color research and application
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.393
H-Index - 62
eISSN - 1520-6378
pISSN - 0361-2317
DOI - 10.1002/col.22068
Subject(s) - yarn , artificial intelligence , weaving , computer vision , segmentation , computer science , color space , colored , projection (relational algebra) , engineering , materials science , algorithm , image (mathematics) , composite material , mechanical engineering
Abstract Automat layout detection of color yarns is necessary for weaving and producing processes of yarn‐dyed fabrics. This study presents a novel approach to inspect the layout of color yarns of double‐system‐mélange color fabrics automatically, which is Part III of the series of studies to develop a computer vision‐based system for automatic inspection of color yarn layout for yarn‐dyed fabrics. The inspection of single‐system‐mélange color fabrics has been realized in Part I of the series of studies. Integrating the projection‐based region segmentation method proposed in Part I and the FCM‐based stepwise classification method proposed in Part II, the proposed approach is composed of three steps: (1) fabric region segmentation, (2) fabric region selection, and (3) layout of color yarns recognition. In the first step, the fabric regions are segmented by the projection‐based region segmentation method. In the second step, the reasonable fabric regions are selected by analyzing their color histograms and comparing their weft color's frequency. In the third step, the layout of color yarn is recognized by the FCM‐based stepwise classification method, and the precise layouts of color warps and wefts are produced. The experimental analysis proved that the proposed method can recognize the layout of color yarns of double‐system‐mélange color fabrics correctly by testing four different color fabrics and three pieces of same yarn‐dyed fabrics. © 2016 Wiley Periodicals, Inc. Col Res Appl, 42, 250–260, 2017