Defects Detection based on Principal Component Analyses and Support Vector Machines

摘要：

Woods are used in many fields. The appearance of woods is important for the quality of wood products. In this paper, we present an image series fusion method based principal component analyses and recognize the defects by support vector machines. We select the histogram of the feature image as feature vector, and send it to support vector machines for recognition and classification. The results show that this method can fuse the image series and detect the defects.

关键词： Principal component analyses Image series Fusion Support vector machines defects detection

作者: Binjie Xiao

作者单位: Department of Control Science and Engineering College of Electronics and Information Engineering 200092, Shanghai, China

会议类型: 国际会议

会议名称: 2010 International Conference on Computer and Communication Technologies in Agriculture Engineering(计算机与通信技术在农业工程国际会议 CCTAE 2010)

会议地点: 成都

会议语种:英文

页码: 296-299

在线出版日期: 2010-06-12（万方平台首次上网日期，不代表论文的发表时间）