A Novel Neutrosophic Subsets Definition for Dermoscopic Image Segmentation

Abstract

Dermoscopic images suffer from irregular and vague boundaries. New directions established the neutrosophic set (NS) approaches for clustering, and segmenting the dermoscopic images. In this work, an accurate segmentation process was developed by mapping initially the dermoscopic images to the NS domain. Thus, the neutrosophic image was defined by three subsets, namely True (T), Indeterminacy (I) and False (F). For accurate boundary detection and segmentation, different high pass (HP) filter types were used in the definition of I subset and low pass (LP) filter types in the definition of T. These filters form a new way to obtain an NS image for segmenting dermoscopy images. A comparative study was carried on the ISIC2016 skin lesion dermoscopic images dataset using different combinations of NS filter types and sizes. The results depicted the superiority of using an unsharp filter in implementing the I subset and an average filter for the T subset. 96% segmentation accuracy was reported using the proposed design compared to 92% accuracy using the default NS definition.

Keywords

• Neutrosophic set
• dermoscopic images
• unsharp filter
• average filter
• image segmentation