Prateeksha Dhantre, R. Prasad, P. Saurabh, B. Verma
{"title":"A hybrid approach for human skin detection","authors":"Prateeksha Dhantre, R. Prasad, P. Saurabh, B. Verma","doi":"10.1109/CSNT.2017.8418526","DOIUrl":null,"url":null,"abstract":"Human skin detection strives to spot skin from the pictures. Automatic skin detection is considered as a significantly difficult and complex as skin image differ on the aspects of contents due to variation in size, style, orientation, alignment coupled with different contrast and background. This paper proposes a skin detection approach using localization, tracking, extraction, enhancement, and recognition. This approach remains sensitive to the color palette and uses edge detection technique. Also, color classification box incorporates a deep impact on the performance of the rule. The proposed approach detects single as well as multiple persons in a picture. Promising results are obtained on variety of pictures, except in few pictures wherever color distinction is hard to even when edge detection rule.","PeriodicalId":382417,"journal":{"name":"2017 7th International Conference on Communication Systems and Network Technologies (CSNT)","volume":"172 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 7th International Conference on Communication Systems and Network Technologies (CSNT)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CSNT.2017.8418526","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
Human skin detection strives to spot skin from the pictures. Automatic skin detection is considered as a significantly difficult and complex as skin image differ on the aspects of contents due to variation in size, style, orientation, alignment coupled with different contrast and background. This paper proposes a skin detection approach using localization, tracking, extraction, enhancement, and recognition. This approach remains sensitive to the color palette and uses edge detection technique. Also, color classification box incorporates a deep impact on the performance of the rule. The proposed approach detects single as well as multiple persons in a picture. Promising results are obtained on variety of pictures, except in few pictures wherever color distinction is hard to even when edge detection rule.