Fast and Non-invasive Surface Crack Detection of Press Panels Using Image Processing

Abstract

The crack detection during the manufacturing process is an important step for quality management of panel products. Traditional crack detection methods are subjective and expensive because they are performed by experienced human inspectors. Therefore, crack detection techniques for automated and accurate inspection are required. In this paper, a crack detection technique based on image processing is proposed, which utilizes the images of panel products captured by a regular CCTV camera system. First, the binary panel object image is extracted from various backgrounds after considering RGB color factors. Edge lines are then generated from a binary image using a percolation process. Finally, crack detection and localization are performed with a unique edge line evaluation. In order to demonstrate the capability of the proposed technique, lab-scale experiments were carried out with a thin aluminum plate and a real sample panel. In addition, the test was performed with the images acquired at an actual press line. Experimental results show that the proposed technique could effectively detect panel cracks with an improved rate and speed.