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Comparison of Different Segmentation Algorithms for Dermoscopic Images
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This paper compares different algorithms for the segmentation of skin lesions in dermoscopic images. The basic segmentation algorithms compared are Thresholding techniques (Global and Adaptive), Region based techniques (K-means, Fuzzy C means, Expectation Maximization and Statistical Region Merging), Contour models (Active Contour Model and Chan - Vese Model) and Spectral Clustering. Accuracy, sensitivity, specificity, Border error, Hammoude distance, Hausdorff distance, MSE, PSNR and elapsed time metrices were used to evaluate various segmentation techniques.
Keywords
Thresholding, Expectation Maximization, Contour Models, Dermoscopy, Spectral Clustering.
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