Crack Detection on Pressed Panel Products using Image Processing Techniques with Camera System

Abstract

The detection of cracks on panel products is a vital step for ensuring the quality of panel products. General crack detection technique has been performed by human inspectors who are good at detecting crack, which is spend
many times and much money. Therefore, it is necessary to detect efficiently crack on panel products by machine vision system during the press forming process. In this study, we performed an automated crack detection using two image processing techniques with camera system. The first technique is evaluating the panel edge lines which are extracted from a percolated object panel image. This technique does not require a reference image for crack
detection. Another technique is based on the comparison between a reference and a test image using the local amplitude mapping on the edge line image. The reference image of panel product is automatically acquired by camera system using image difference and time interval technique. As a result, cracks are efficiently detected using two crack detection techniques based on image processing. For demonstrating the proposed techniques, experiments were performed in the laboratory and the actual manufacturing lines. Experimental results show that the proposed techniques could effectively improve the crack detection rate with improved speed.