64 A Novel Automated Morphological Fuzzy Optimal Thresholding Technique to Extract Malignant Melanoma Lesions
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A novel automated Fuzzy Optimal Thresholding Technique to differentiate malignant melanoma lesions from the normal skin is proposed in this paper. Segmentation of pigmented skin lesion images pertaining to malignant melanoma diagnosis is achieved with the help of fuzzy Optimal Threshold value and Mathematical morphology. The input melanoma skin lesion color images are acquired and preprocessed to remove noise as well as some unwanted structures like hairs, etc. The preprocessed image is smoothened by morphological operations, converted into a gray scale image and binarized by using Fuzzy Optimal Threshold value obtained by Fuzzy Gaussian Measures. The largest label region, a cancer area from the binary image is identified and the borders are extracted and imposed on the original skin lesion image. The efficiency of the algorithm is tested over 100 images and proved up to 90% of the accurate extraction of skin lesion borders.