[직/편성물] Application of computer vision in the automatic identification and classification of woven fabric weave patterns 출판일 : 2010.12.01 저자 : Chung-Feng Jeffrey Kuo, Chung-Yang Shih, Cheng-En Ho, Kai-Ching Peng 서지사항 : Textile Research Journal, Volume 80, Issue 20, 2144 페이지 등록일 : 2011.04.13 I 조회수 : 678 작성자 : admin |
Traditionally, fabric texture identification is based on visual inspection. Recent studies have
proposed automatic recognition, which utilizes computer vision to recognize the texture of
different fabrics. In the recognition process, the fabric weave patterns are identified by the
warp and weft floats. However, due to the optical environments and the appearance
differences of fabrics and yarns, the stability and fault-tolerance of the computer vision
method are yet to be improved. By using the fabric weave patterns image identification
system, this study analyzed the fabric image to find out the warp and weft by the pixel gray-
level cumulative values. It then cut out the image of the warp and weft floats to obtain the
texture feature values, and used the Fuzzy C-Means (FCM) algorithm to identify the warp
and weft floats. The identification results can derive the black-white digital image and the
digital matrix of the fabric weave patterns. Finally, weaves classification is conducted
based on the successfully trained two-stage Back-Propagation Neural Network. This two-
stage neural network can be used to construct the computer vision system to recognize
fabric texture, and to increase the system reliability and accuracy. This study used the first-
order and second-order co-occurrence matrix, and confirmed that fabric patterns can be
identified and classified accurately with this method.
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