Printing Defects Inspection Based on Improved Multi-Class Support Vector Machine

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.