An intelligent machine vision system for detecting surface defects on packing boxes based on support vector machine. (September 2019)

• Record Type: Journal Article
• Authors: Wu, Yu; Lu, Yanjie
• Is Part Of: Measurement and control. Volume 52:Number 7/8(2019)
• Page Start: 1102
• Page End: 1110
• Publication Date: 2019-09
• Subjects: Machine vision -- machine learning -- surface defect detection -- support vector machine; Automatic control -- Periodicals; Engineering instruments -- Periodicals; Production engineering -- Periodicals; 629.8
• DOI: 10.1177/0020294019858175
• Languages: English
• ISSNs: 0020-2940

Abstract

Defects in product packaging are one of the key factors that affect product sales. Traditional defect detection depends primarily on artificial vision detection. With the rapid development of machine vision, image processing, pattern recognition, and other technologies, industrial automation detection has become an inevitable trend because machine vision technology can greatly improve accuracy and efficiency; therefore, it is of great practical value to study automatic detection technology of the surface defects encountered in packaging boxes. In this study, machine vision and machine learning were combined to examine a surface defect detection method based on support vector machine where defective products are eliminated by a sorting robot system. After testing, the support vector machine training model using radial basis function kernel detects three kinds of defects at the same time under the ideal condition of parameter selection, and the effective detection rate is 98.0296%.