{"title":"光谱聚类分割彩色图像的色彩空间选择","authors":"L. Busin, J. Shi, N. Vandenbroucke, L. Macaire","doi":"10.1109/ICSIPA.2009.5478603","DOIUrl":null,"url":null,"abstract":"In this paper, we propose to segment color images by pixel clustering in a selected color space. This color space is selected among a set of classical color spaces according to a specific criterion based on a spectral clustering analysis. The clusters are determined by analyzing the 3D-histogram of the image coded in the selected color space thanks to a spectral clustering method. This scheme can identify clusters with complex shapes in the color space without any other post/pre-processing stages.","PeriodicalId":400165,"journal":{"name":"2009 IEEE International Conference on Signal and Image Processing Applications","volume":"120 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2009-11-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"23","resultStr":"{\"title\":\"Color space selection for color image segmentation by spectral clustering\",\"authors\":\"L. Busin, J. Shi, N. Vandenbroucke, L. Macaire\",\"doi\":\"10.1109/ICSIPA.2009.5478603\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper, we propose to segment color images by pixel clustering in a selected color space. This color space is selected among a set of classical color spaces according to a specific criterion based on a spectral clustering analysis. The clusters are determined by analyzing the 3D-histogram of the image coded in the selected color space thanks to a spectral clustering method. This scheme can identify clusters with complex shapes in the color space without any other post/pre-processing stages.\",\"PeriodicalId\":400165,\"journal\":{\"name\":\"2009 IEEE International Conference on Signal and Image Processing Applications\",\"volume\":\"120 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2009-11-02\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"23\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2009 IEEE International Conference on Signal and Image Processing Applications\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICSIPA.2009.5478603\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2009 IEEE International Conference on Signal and Image Processing Applications","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICSIPA.2009.5478603","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Color space selection for color image segmentation by spectral clustering
In this paper, we propose to segment color images by pixel clustering in a selected color space. This color space is selected among a set of classical color spaces according to a specific criterion based on a spectral clustering analysis. The clusters are determined by analyzing the 3D-histogram of the image coded in the selected color space thanks to a spectral clustering method. This scheme can identify clusters with complex shapes in the color space without any other post/pre-processing stages.