AUTOMATIC SEGMENTATION OF SKIN LESIONS USING HISTOGRAM THRESHOLDING

Abstract

Automatic lesion segmentation is an important part of computer-based image analysis of pigmented skin lesions. Currently, there is a great interest in the development of Computer-Aided Diagnosis (CAD) systems for dermoscopic images. The segmentation step is one of the most important ones, since its accuracy determines the eventual success or failure of a CAD system. This study introduced new method of dermoscopic images segmentation. The preprocess was the filtering operation to dermoscopy image to remove most of difficulties facing the efficient segmentations, like a variety of lesion shapes, sizes, color, changes due to different skin types and textures and presence of hairs. Segmentation based mainly on histogram thresholding. The enhancements of image achieved by using mathematical morphology in order to obtain better segmentation with smooth border and without any noise in the lesion region. The proposed method evaluated by using Hammoude Distance (HM) and the True Detection Rate (TDR). Also the proposed method is compared with other skin lesions segmentation methods such as Otsu, adaptive thresholding and fuzzy C-means. The accuracy of proposed method was 96.32%, which is highly promised result and dependable.