{"title":"基于二类模糊集的彩色图像分割","authors":"Jerome Clairet, A. Bigand, O. Colot","doi":"10.1109/ICELIE.2006.347211","DOIUrl":null,"url":null,"abstract":"This paper focuses on application of fuzzy sets of type 2 in color images segmentation. It is well-known that images segmentation is one of the most difficult low-level image analysis tasks. Many disturbing factors, or image vagueness may corrupt this task. So we propose a new color image segmentation scheme based on type-2 fuzzy sets, that allows to take into account the total uncertainty inherent to this operation. First, type-2 fuzzy sets are presented. Then the algorithm of fuzzy segmentation is explained and finally some interesting results are presented","PeriodicalId":345289,"journal":{"name":"2006 1ST IEEE International Conference on E-Learning in Industrial Electronics","volume":"10 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2006-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"26","resultStr":"{\"title\":\"Color Image Segmentation using Type-2 Fuzzy Sets\",\"authors\":\"Jerome Clairet, A. Bigand, O. Colot\",\"doi\":\"10.1109/ICELIE.2006.347211\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper focuses on application of fuzzy sets of type 2 in color images segmentation. It is well-known that images segmentation is one of the most difficult low-level image analysis tasks. Many disturbing factors, or image vagueness may corrupt this task. So we propose a new color image segmentation scheme based on type-2 fuzzy sets, that allows to take into account the total uncertainty inherent to this operation. First, type-2 fuzzy sets are presented. Then the algorithm of fuzzy segmentation is explained and finally some interesting results are presented\",\"PeriodicalId\":345289,\"journal\":{\"name\":\"2006 1ST IEEE International Conference on E-Learning in Industrial Electronics\",\"volume\":\"10 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2006-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"26\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2006 1ST IEEE International Conference on E-Learning in Industrial Electronics\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICELIE.2006.347211\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2006 1ST IEEE International Conference on E-Learning in Industrial Electronics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICELIE.2006.347211","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
This paper focuses on application of fuzzy sets of type 2 in color images segmentation. It is well-known that images segmentation is one of the most difficult low-level image analysis tasks. Many disturbing factors, or image vagueness may corrupt this task. So we propose a new color image segmentation scheme based on type-2 fuzzy sets, that allows to take into account the total uncertainty inherent to this operation. First, type-2 fuzzy sets are presented. Then the algorithm of fuzzy segmentation is explained and finally some interesting results are presented
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