This paper presents an algorithm for the detection of micro-crack defects in the multicrystalline solar cells. This\ndetection goal is very challenging due to the presence of various types of image anomalies like dislocation clusters,\ngrain boundaries, and other artifacts due to the spurious discontinuities in the gray levels. In this work, an algorithm\nfeaturing an improved anisotropic diffusion filter and advanced image segmentation technique is proposed. The methods\nand procedures are assessed using 600 electroluminescence images, comprising 313 intact and 287 defected samples.\nResults indicate that the methods and procedures can accurately detect micro-crack in solar cells with sensitivity,\nspecificity, and accuracy averaging at 97%, 80%, and 88%, respectively.
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