Surface defects detection for mobilephone panel workpieces based on machine vision and machine learning

Abstract

The advances in digital image processing technology, the increasing availability of computing resources and highdefinition resolution cameras have resulted in a great deal of interest in object detection algorithms in defects inspection of industrial products. This paper proposes a complete framework to cope with the surface defects detection of mobile phone panel workpieces. The proposed method has a set of consecutive handling processes： original image cutting and standardization, image blocks segmentation and feature extraction, machine learning embedded defects detection. We empirically prove the capability of the proposed method for detecting defects of mobile phone panel surface. The comparison with different algorithms further show that our method achieves excellent performance for mobile phone panel surface defects detection task in both detecting accuracy and detecting speed.