{"title":"Circular histogram thresholding for color image segmentation","authors":"Din-Chang Tseng, Yao-Fu Li, Cheng-Tan Tung","doi":"10.1109/ICDAR.1995.601986","DOIUrl":null,"url":null,"abstract":"A circular histogram thresholding for color image segmentation is proposed. A circular hue histogram is first constructed based on a UCS (I,H,S) color space. The histogram is automatically smoothed by a scale-space filter, then transformed into traditional histogram form, and finally recursively thresholded based on the maximum principle of variance. Three comparisons of performance are reported: (i) the proposed thresholding on the circular histogram with that on a traditional histogram; (ii) the proposed thresholding with clustering; and (iii) thresholding based on a UCS hue attribute with that based on a non-UCS hue attribute. Benefits of the proposed approach are confirmed in experiments.","PeriodicalId":273519,"journal":{"name":"Proceedings of 3rd International Conference on Document Analysis and Recognition","volume":"36 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1995-08-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"42","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of 3rd International Conference on Document Analysis and Recognition","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICDAR.1995.601986","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 42
Abstract
A circular histogram thresholding for color image segmentation is proposed. A circular hue histogram is first constructed based on a UCS (I,H,S) color space. The histogram is automatically smoothed by a scale-space filter, then transformed into traditional histogram form, and finally recursively thresholded based on the maximum principle of variance. Three comparisons of performance are reported: (i) the proposed thresholding on the circular histogram with that on a traditional histogram; (ii) the proposed thresholding with clustering; and (iii) thresholding based on a UCS hue attribute with that based on a non-UCS hue attribute. Benefits of the proposed approach are confirmed in experiments.