Automatic inspection of fabric defects based on computer vision

摘要：

Wavelet transform and BP neural network were used together to inspect and classify the fabric defects. A plain white fabric is adopted as the sample, and the distinguishing defects are oil stains, warplacking, and weft-lacking. An area camera with 256×256 resolution is used in the scheme, a grabbed image is transmitted to a computer for wavelet transform, and then the corresponding image data are then used in BP neural network as input. The result shows that the fabric defects classification rate can be up to 95% with above method.

关键词： wavelet analysis BP neural network fabric defects

作者: LIU Shu-guang QU Ping-ge

作者单位: School of Electronic and Infonnation,Xian Polytechnic University, Xian 710048,China

会议类型: 国际会议

会议名称: 2009 International Teztile Science and Technology Forum(2009国际纺织科学技术论坛)

会议地点: 西安

会议语种:英文

页码: 196-201

在线出版日期: 2009-04-01（万方平台首次上网日期，不代表论文的发表时间）