An approach to unsupervised hair removal from skin melanoma image

Hair removal from skin melanoma image is one of the key problems for the precise segmentation and analysis of the skin malignant melanoma. In this paper, an automatically hair removal algorithm in dermoscopy images of pigmented skin lesions is proposed. This algorithm includes three steps: firstly, the melanoma image with hairs are enhanced by morphologic closing-based top-hat operator and then segmented through statistic threshold; secondly, the hairs are extracted based on the elongate of connected region; thirdly, the hair-occluded information is repaired by replacing the hair pixels with the nearby non-hair pixels. As a matter of fact, with the morphologic closing-based top-hat operator both strong and weak hairs can be enhanced simultaneously, and the elongate state of band-like connected region can be correctly described by the elongate function proposed in this paper so as to measure the hair effectively. Therefore, the unsupervised hair removal problem in dermoscopy melanoma image can be resolved very well through combining the hair extraction with information repair. The experiment results show that various hairs can be extracted accurately and the repaired effect of textures can satisfy the requirement of medical diagnosis.