Revisited Otsu Algorithm for Skin Cancer Segmentation

Abstract

Computer-aided technology can be used to perform a quantitative and objective evaluation of pigmented skin lesions during the clinical assessment procedure. This helps to expedite the procedure. The growing development of non-invasive techniques can be of significant benefit in the early identification of malignant melanoma, which can, in turn, help to minimize the necessity for invasive biopsies. The system is primarily focused on two principal schemes: Establishing an effective lesion border detection method and then creating an efficient classification scheme. We address two primary areas in this work. First, we study skin lesion detection to analyze any sign of malignancy for skin cancer diagnosis. This is followed by the system implementation of a color-based method for all the images from the RGB color space using a revisited OTSU thresholding segmentation scheme. The results proved to be promising with at least an 80% accuracy detection rate for a wide range of clinical skin lesion images.