Automatic Recognition of Textile Texture Using Back-propagation Neural Network
This study proposed to use wavelet transfer to acquire image features, and use back-propagation neural network to classify type of textile texture. Firstly, wavelet transfer is applied to obtain vertical, horizontal and diagonal images of original image, and compute its wavelet energy to take them as texture features of this image. Finally, the backpropagation neural network is adopted to recognize texture feature of this image. As indicated by experimental result, this system can recognize accurately texture in woven fabric. Among 350 test samples in total, the general recognition rate amounts to 96％. Therefore, this study succeeded in building the automatic computer visual inspection system to recognize textile texture type, which can greatly improve and avoid current low efficiency, non-objective judgment and labor waste due to human inspection.
neural network wavelet transform textile texture
Te-Li Su Gui-Bing Hong Wen-Ya Chang Fu-Chen Kung
Department of Cosmetic Application and Management St. Marys Medicine, Nursing and Management Colleg Department of Health Development and Health Marketing Kainan University Taoyuan 33857, Taiwan
国际会议
上海
英文
52-55
2011-03-11（万方平台首次上网日期，不代表论文的发表时间）