Abstract：Aiming at the problem of color difference detection on polycrystalline silicon cells under complex color and texture characteristics, a new method based on support vector machine classification strategy is proposed to detect the color difference of polycrystalline silicon cells. Firstly, color model conversion and channel separation are performed on the pre-processed cell images. The Otsu method is used to perform threshold segmentation processing on the single-channel image, and the region contrast of each threshold image is calculated, and then an appropriate threshold image is selected according to the regional contrast condition. The image features are extracted by the information provided by the threshold image. Finally, the support vector machine classifier is used to determine whether the cell has a color difference defect. The experimental results show that the proposed color difference detection algorithm can achieve high-efficiency detection of color difference defect, and the accuracy, false detection rate and detection time reach 96.88%, 5% and 109 ms.
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2019, Vol. 40 
