{"title":"基于颗粒点阵矩阵空间的图像分割算法","authors":"Keming Xie, Xiaoli Hao, Jun Xie","doi":"10.1109/GRC.2009.5255049","DOIUrl":null,"url":null,"abstract":"For granular computing has advantage to handle a great deal of fuzzy information, it provides new thoughts for image segmentation. Firstly, the paper defines a new granular computing model, which is granular lattice matrix model. Secondly, we applied the model to image segmentation and proposed a new algorithm of segmentation. Finally, we certify the new algorithm is better than traditional algorithm on edge fining by tests.","PeriodicalId":388774,"journal":{"name":"2009 IEEE International Conference on Granular Computing","volume":"105 2","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2009-09-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Image segmentation algorithm based on granular lattice matrix space\",\"authors\":\"Keming Xie, Xiaoli Hao, Jun Xie\",\"doi\":\"10.1109/GRC.2009.5255049\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"For granular computing has advantage to handle a great deal of fuzzy information, it provides new thoughts for image segmentation. Firstly, the paper defines a new granular computing model, which is granular lattice matrix model. Secondly, we applied the model to image segmentation and proposed a new algorithm of segmentation. Finally, we certify the new algorithm is better than traditional algorithm on edge fining by tests.\",\"PeriodicalId\":388774,\"journal\":{\"name\":\"2009 IEEE International Conference on Granular Computing\",\"volume\":\"105 2\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2009-09-22\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2009 IEEE International Conference on Granular Computing\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/GRC.2009.5255049\",\"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 Granular Computing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/GRC.2009.5255049","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Image segmentation algorithm based on granular lattice matrix space
For granular computing has advantage to handle a great deal of fuzzy information, it provides new thoughts for image segmentation. Firstly, the paper defines a new granular computing model, which is granular lattice matrix model. Secondly, we applied the model to image segmentation and proposed a new algorithm of segmentation. Finally, we certify the new algorithm is better than traditional algorithm on edge fining by tests.
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