Saliency-based segmentation of dermoscopic images using color information
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Skin lesion segmentation is one of the crucial steps for an efficient non-invasive computer-aided early diagnosis of melanoma. In this paper, we investigate how saliency and color information can be usefully employed to determine the lesion region. Unlike most existing saliency-based methods, to discriminate against the skin lesion from the surrounding regions we enucleate some properties related to saliency and color information and we propose a novel segmentation process using binarization coupled with new perceptual criteria based on these properties. To refine the accuracy of the proposed method, the segmentation step is preceded by a pre-processing aimed at reducing the computation burden, removing artifacts, and improving contrast. We have assessed the method on two public databases including 1497 dermoscopic images and compared its performance with that of classical saliency-based methods and with that of some more recent saliency-based methods specifically applied to dermoscopic images. Results of qualitative and quantitative evaluations of the proposed method are promising as the obtained skin lesion segmentation is accurate and the method performs satisfactorily in comparison to other existing saliency-based segmentation methods.
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