K-means Clustering-based Color Segmentation on Vitiligo Skin Lesion

Vitiligo affects around 1% of the world’s population, significantly affecting children’s and adults’ quality of life. Vitiligo has gotten a lot of attention as a significant skin lesion in the field of pigmented skin disorders and is the area of interest for most researchers. Not only does it have certain characteristics with other skin diseases, such as poor contrast and uneven skin lesions, but it is often difficult to capture dermoscopy images for examination under carefully controlled lighting circumstances due to the lesion’s enormous size. The precision with which skin lesions like vitiligo may be identified from dermoscopic pictures is directly related to the accuracy with which skin lesions can be segmented. This article provides a method for segmenting skin lesions using a clustering algorithm. The proposed algorithm’s results for skin lesion segmentation were compared to annotated images. The findings are compelling, with reasonable computation time indicating that the suggested work may be used in real-time.