A New Method of Paper Defect Recognition Based on Wavelet Packet Decomposition and BP Neural Network

摘要：

A new approach of paper defect recognition is . proposed. To implement this method, computer is used to acquire paper image and the subtraction algorithm is used to determine if the image contains defect at first. For the image with paper defect, wavelet packet decomposition is applied to extracting the feature vector of the defect A BP neural network is designed for recognizing the defect type according to the feature vector. This approach provides a unified detection algorithm for different types of paper defects. The experiment data prove this method is valid and can be applied in modern paper defect inspection system.

关键词： paper defect recognition feature vector wavelet packet decomposition BP neural network

作者: Wang Xiaofang Qiu Shubo Wang Qiang

作者单位: Shandong Provincial Key Laboratory of AM&MC Technology for Light Industry Equipment, Shandong Instit Affiliated Hospital Binzhou Medical College Binzhou Shandong, China

会议类型: 国际会议

会议名称: 2011 3rd International Conference on Computer and Automation Engineering(ICCAE 2011)(2011年第三届IEEE计算机与自动化工程国际会议)

会议地点: 重庆

会议语种:英文

页码: 345-349

在线出版日期: 2011-01-21（万方平台首次上网日期，不代表论文的发表时间）