Skin Lesion Image Segmentation Based on C-Means Clustering Algorithm
Deepak Kourav1, Abhinav Kathal2
1Dr. Deepak Kourav*, Department of Electronics and Communication Engineering, NRI Institute of Research and Technology, Bhopal, India.
2Abhinav Kathal, Department of Electronics and Communication Engineering, NRI Institute of Research and Technology, Bhopal, India.
Manuscript received on September 15, 2019. | Revised Manuscript received on 23 September, 2019. | Manuscript published on October 10, 2019. | PP: 987-990 | Volume-8 Issue-12, October 2019. | Retrieval Number: K13060981119/2019©BEIESP | DOI: 10.35940/ijitee.K1306.1081219
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: A skin lesion is an abnormal lump, bump, and ulcer, sore or colored area on the skin. There are many types of skin segmentation. In computer vision, image segmentation is the process of partitioning a digital image into multiple segments (sets of pixels, also known as super-pixels). The goal of segmentation is to simplify and/or change the representation of an image into something that is more meaningful and easier to analyze. In this ipaper using C-Means Clustering approach for skin lesion image segmentation so that detection and recognition of skin decease will easy to understand by patient and biomedical industries.
Keywords: Skin. Lesion. Segmentation, C-means, Cluster.
Scope of the Article: Clustering