{"title":"基于磁共振成像的混沌多智能体图像分割方法","authors":"K. Melkemi, M. Batouche, S. Foufou","doi":"10.1109/ISPA.2005.195421","DOIUrl":null,"url":null,"abstract":"In this paper, we propose a new chaotic approach for image segmentation based on multiagent system (MAS). We consider a set of segmentation agents organized around a coordinator agent. Each segmentation agent performs iterated conditional modes (ICM) starting from its own initial image created using a chaotic mapping. The coordinator agent diversifies the initial images using a crossover and a chaotic mutation operators. The efficiency of our chaotic MAS approach is shown through some experimental results.","PeriodicalId":238993,"journal":{"name":"ISPA 2005. Proceedings of the 4th International Symposium on Image and Signal Processing and Analysis, 2005.","volume":"56 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2005-10-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":"{\"title\":\"Chaotic multiagent system approach for MRF-based image segmentation\",\"authors\":\"K. Melkemi, M. Batouche, S. Foufou\",\"doi\":\"10.1109/ISPA.2005.195421\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper, we propose a new chaotic approach for image segmentation based on multiagent system (MAS). We consider a set of segmentation agents organized around a coordinator agent. Each segmentation agent performs iterated conditional modes (ICM) starting from its own initial image created using a chaotic mapping. The coordinator agent diversifies the initial images using a crossover and a chaotic mutation operators. The efficiency of our chaotic MAS approach is shown through some experimental results.\",\"PeriodicalId\":238993,\"journal\":{\"name\":\"ISPA 2005. Proceedings of the 4th International Symposium on Image and Signal Processing and Analysis, 2005.\",\"volume\":\"56 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2005-10-24\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"4\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"ISPA 2005. Proceedings of the 4th International Symposium on Image and Signal Processing and Analysis, 2005.\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ISPA.2005.195421\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"ISPA 2005. Proceedings of the 4th International Symposium on Image and Signal Processing and Analysis, 2005.","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ISPA.2005.195421","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Chaotic multiagent system approach for MRF-based image segmentation
In this paper, we propose a new chaotic approach for image segmentation based on multiagent system (MAS). We consider a set of segmentation agents organized around a coordinator agent. Each segmentation agent performs iterated conditional modes (ICM) starting from its own initial image created using a chaotic mapping. The coordinator agent diversifies the initial images using a crossover and a chaotic mutation operators. The efficiency of our chaotic MAS approach is shown through some experimental results.