Research on Image Defect Detection of Silicon Panel Based on Prewitt and Canny Operator - Zhang, Yifeng; Wang, Zhiwen; Wang, Yuhang; Zhang, Canlong; Zhao, Biao (Frontiers in Physics, 2021)
Silicon panel is the core component of photovoltaic power generation, whose surface quality is related to its service life and power generation efficiency. However, micro-cracks, fragments, incomplete welding, broken grids and other defects often occur in industrial production. The edge detection algorithm is usually used to detect the defects of silicon panels, but the common edge detection algorithm has an impact on the defect detection because of the grid shadow of the panel. To solve the problem, a defect detection method based on Prewitt and Canny operator is proposed in this paper. In this method, Prewitt operator and Canny operator are combined to eliminate the effect of grid on the detection. The micro-crack defects and its specific positions can be detected efficiently and intuitively, therefore improving the detection accuracy of mirco-crack in panels by doing so. The experimental results indicate that the purity and integrity of the defect profile of the image processed by the algorithm are greatly improved. The foreground edge is clearer, and the defect recognition accuracy is higher, which effectively prevent the impact of grid shadow on weld testing.