A CISG Method for Internal Defect Detection of Solar Cells in Different Production Processes

Abstract

The internal defect detection of solar cells indifferent production processes currently adopts manual visual verification on the images captured by electroluminescence or photoluminescence system. To improve the efficiency and reliability of the inspection, this article proposes a generic and automatic component-of-interest superposition graph(CISG) method. First, the solar cell inspection region is located by shape-based matching. Second, based on the properties of Fourier transform and singular value decomposition, the frequency components of the testing image are modified adaptively, and then component graphs with different local saliency are generated. According to the normalized marginal gains of energy, these component graphs are combined into a saliency map. Finally, defective regions are extracted from the saliency map using the global threshold technique. By employing various compared approaches to conduct experiments on five datasets from different production processes, the great performance of our presented method is revealed, which also implies this method outperforms the current methods.