{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/automatic-skin-lesion-segmentation-using-1","title":"Automatic Skin Lesion Segmentation Using GrabCut in HSV Colour Space","arxiv_id":"1810.00871","date":"2018-09-30","proceeding":null,"authors":["Fakrul Islam Tushar"],"abstract":"Skin lesion segmentation is one of the first steps towards automatic\nComputer-Aided Diagnosis of skin cancer. Vast variety in the appearance of the\nskin lesion makes this task very challenging. The contribution of this paper is\nto apply a power foreground extraction technique called GrabCut for automatic\nskin lesion segmentation with minimal human interaction in HSV color space.\nPreprocessing was performed for removing the outer black border. Jaccard Index\nwas measured to evaluate the performance of the segmentation method. On\naverage, 0.71 Jaccard Index was achieved on 1000 images from ISIC challenge\n2017 Training Dataset.","url_abs":"http://arxiv.org/abs/1810.00871v1","url_pdf":"http://arxiv.org/pdf/1810.00871v1.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"automatic-skin-lesion-segmentation-using-1","repo_url":"https://github.com/fitushar/Skin-lesion-Segmentation-using-grabcut","is_official":1,"mentioned_in_paper":0,"mentioned_in_github":0,"framework":"none","reach":null}],"tasks":[{"task_slug":"lesion-segmentation","task_name":"Lesion Segmentation"},{"task_slug":"segmentation","task_name":"Segmentation"},{"task_slug":"skin-lesion-segmentation","task_name":"Skin Lesion Segmentation"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}