{"title":"基于曲线演化和各向异性扩散的图像分割方法","authors":"Yongsheng Pan, J. Birdwell, S. Djouadi","doi":"10.1109/ISM.2005.68","DOIUrl":null,"url":null,"abstract":"In this paper, a new model is proposed for image segmentation that integrates the curve evolution and anisotropic diffusion methods. The curve evolution method, utilizing both gradient and region information, segments an image into multiple regions. During the evolution of the curve, anisotropic diffusion is adaptively applied to the image to remove noise while preserving boundary information. Coupled partial differential equations (PDE's) are used to implement the method. Experimental results show that the proposed model is successful for complex images with high noise","PeriodicalId":322363,"journal":{"name":"Seventh IEEE International Symposium on Multimedia (ISM'05)","volume":"12 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2005-12-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"6","resultStr":"{\"title\":\"Image Segmentation Using Curve Evolution and Anisotropic Diffusion: An Integrated Approach\",\"authors\":\"Yongsheng Pan, J. Birdwell, S. Djouadi\",\"doi\":\"10.1109/ISM.2005.68\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper, a new model is proposed for image segmentation that integrates the curve evolution and anisotropic diffusion methods. The curve evolution method, utilizing both gradient and region information, segments an image into multiple regions. During the evolution of the curve, anisotropic diffusion is adaptively applied to the image to remove noise while preserving boundary information. Coupled partial differential equations (PDE's) are used to implement the method. Experimental results show that the proposed model is successful for complex images with high noise\",\"PeriodicalId\":322363,\"journal\":{\"name\":\"Seventh IEEE International Symposium on Multimedia (ISM'05)\",\"volume\":\"12 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2005-12-12\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"6\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Seventh IEEE International Symposium on Multimedia (ISM'05)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ISM.2005.68\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Seventh IEEE International Symposium on Multimedia (ISM'05)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ISM.2005.68","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Image Segmentation Using Curve Evolution and Anisotropic Diffusion: An Integrated Approach
In this paper, a new model is proposed for image segmentation that integrates the curve evolution and anisotropic diffusion methods. The curve evolution method, utilizing both gradient and region information, segments an image into multiple regions. During the evolution of the curve, anisotropic diffusion is adaptively applied to the image to remove noise while preserving boundary information. Coupled partial differential equations (PDE's) are used to implement the method. Experimental results show that the proposed model is successful for complex images with high noise