华东理工大学学报（自然科学版）2017，Vol.43Issue(1)：143-148,6.DOI:10.14135/j.cnki.1006-3080.2017.01.022
基于改进多类支持向量机的印刷缺陷检测
Printing Defects Inspection Based on Improved Multi-Class Support Vector Machine
胡方尚 1郭慧1
作者信息
- 1. 华东理工大学机械与动力工程学院,上海 200237
- 折叠
摘要
Abstract
To recognize the defects of printed matter effectively,a method of printing defect inspection based on the improved multi-class support vector machine is proposed.According to the human visual characteristics,the binary defect image is rapidly obtained by the subtraction operation of registered image based on dynamic threshold.A feature vector consisting of defect geometric feature and shape feature is used to describe the defect of printing,and finally the accurate identification of printing defects is realized by the improved multi-class support vector machine.The experimental results show that in the case of less training samples the proposed method has faster detection speed and higher recognition accuracy than OVOSVM and OVRSVM,which can effectively solve the problem of printing defect inspection.关键词
缺陷检测/差分运算/支持向量机/动态阈值/印刷品Key words
defect inspection/subtraction operation/SVM/dynamic threshold/printed matter分类
信息技术与安全科学引用本文复制引用
胡方尚,郭慧..基于改进多类支持向量机的印刷缺陷检测[J].华东理工大学学报（自然科学版）,2017,43(1):143-148,6.
