{"title":"洪水孤立区域重新分配","authors":"S. Makki, David A. Heitbrink, Xiaohua Jia","doi":"10.1109/GRC.2006.1635815","DOIUrl":null,"url":null,"abstract":"Fuzzy C-Means (FCM) clustering is a popular technique used in image segmentation and pattern recognition. However one of the main problems with FCM clustering is the lack of spatial context. That is FCM often fails with irregularly shaped clusters. This can lead to the creation of isolated regions; isolated regions are those regions that are not connected with the main body of the clusters. We propose a post-processing technique whereby these misclassified regions are identified and reassigned to their proper clusters.","PeriodicalId":400997,"journal":{"name":"2006 IEEE International Conference on Granular Computing","volume":"130 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2006-05-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Flooding isolated region reassignment\",\"authors\":\"S. Makki, David A. Heitbrink, Xiaohua Jia\",\"doi\":\"10.1109/GRC.2006.1635815\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Fuzzy C-Means (FCM) clustering is a popular technique used in image segmentation and pattern recognition. However one of the main problems with FCM clustering is the lack of spatial context. That is FCM often fails with irregularly shaped clusters. This can lead to the creation of isolated regions; isolated regions are those regions that are not connected with the main body of the clusters. We propose a post-processing technique whereby these misclassified regions are identified and reassigned to their proper clusters.\",\"PeriodicalId\":400997,\"journal\":{\"name\":\"2006 IEEE International Conference on Granular Computing\",\"volume\":\"130 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2006-05-10\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2006 IEEE International Conference on Granular Computing\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/GRC.2006.1635815\",\"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 IEEE International Conference on Granular Computing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/GRC.2006.1635815","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Fuzzy C-Means (FCM) clustering is a popular technique used in image segmentation and pattern recognition. However one of the main problems with FCM clustering is the lack of spatial context. That is FCM often fails with irregularly shaped clusters. This can lead to the creation of isolated regions; isolated regions are those regions that are not connected with the main body of the clusters. We propose a post-processing technique whereby these misclassified regions are identified and reassigned to their proper clusters.
求助内容：
应助结果提醒方式：
京公网安备 11010802042870号
