In this paper, a methodological approach devoted to the segmentation and the characterization of tumors skin lesions is presented. Melanoma is the most malignant skin tumor, growing in melanocytes cells that are responsible of pigmentation. Nowadays, this type of cancer is increasing rapidly. Besides, its related mortality rate increases by more modest and inversely proportional to the thickness of the tumor. Fortunately, this rate can be decreased by an earlier detection and a better prevention. Indeed, the segmentation is very helpful in the lesion shape information extraction and consequently it is an essential step to locate the tumor. In this domain, we have evaluated several techniques for the segmentation of dermatoscopic images like Region growing, thresholding segmentation…etc. All these methods do not separate exactly the lesion from the background. In this work a fast approaches in border detection of dermoscopy pigmented skin lesions images based on multi-level decomposition and on classification method are presented. These methods are tested on a set of 60 dermoscopy images. The obtained results than that the presented method achieves both fast and accurate border detection.
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