Abstract—A novel method to classify micro-cracks in Photoluminescence (PL) images of polycrystalline solar cells is proposed. Micro-cracks in PL images are difficult distinguish as they’re easily confused with noises that are present which may share the same size and shape features. Instead of relying on shape analysis to classify micro-cracks, the proposed method takes advantage of the patterns that are present at the end points of micro-cracks. Textural features are extracted via grey level co-occurrence matrix at the end points and then used as feature vectors in a SVM classifier. The proposed method is compared against existing shape analysis method and a preliminary experimental result has shown a significant improvement in sensitivity, specificity and accuracy.
Index Terms—solar cell, photoluminescence, micro-crack
Cite: Teow Wee Teo and Mohd Zaid Abdullah, "Solar Cell Micro-Crack Detection Using Localised Texture Analysis," Journal of Image and Graphics, Vol. 6, No. 1, pp. 54-58, June 2018. doi: 10.18178/joig.6.1.54-58
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