{"title":"基于LBF模型的水平集图像分割算法改进研究","authors":"Hongya Wang, Lixia Yu","doi":"10.1109/iske47853.2019.9170464","DOIUrl":null,"url":null,"abstract":"For the images characteristic With intensity inhomogeneity, this paper proposes an improved model of contour evolution LBF energy function, Which combines the global CV model energy term accelerated evolution rate and the combined local mean LBF model information, While the introduction of a global image of the local variance and variance information. Experimental results show that this method can provide accurate smooth closed boundary, precision can reach sub-pixel level. The recognition accuracy rate is high.","PeriodicalId":399084,"journal":{"name":"2019 IEEE 14th International Conference on Intelligent Systems and Knowledge Engineering (ISKE)","volume":"121 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Research on Improved of Level Set Image Segmentation Algorithms Based on LBF Model\",\"authors\":\"Hongya Wang, Lixia Yu\",\"doi\":\"10.1109/iske47853.2019.9170464\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"For the images characteristic With intensity inhomogeneity, this paper proposes an improved model of contour evolution LBF energy function, Which combines the global CV model energy term accelerated evolution rate and the combined local mean LBF model information, While the introduction of a global image of the local variance and variance information. Experimental results show that this method can provide accurate smooth closed boundary, precision can reach sub-pixel level. The recognition accuracy rate is high.\",\"PeriodicalId\":399084,\"journal\":{\"name\":\"2019 IEEE 14th International Conference on Intelligent Systems and Knowledge Engineering (ISKE)\",\"volume\":\"121 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-11-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2019 IEEE 14th International Conference on Intelligent Systems and Knowledge Engineering (ISKE)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/iske47853.2019.9170464\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 IEEE 14th International Conference on Intelligent Systems and Knowledge Engineering (ISKE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/iske47853.2019.9170464","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Research on Improved of Level Set Image Segmentation Algorithms Based on LBF Model
For the images characteristic With intensity inhomogeneity, this paper proposes an improved model of contour evolution LBF energy function, Which combines the global CV model energy term accelerated evolution rate and the combined local mean LBF model information, While the introduction of a global image of the local variance and variance information. Experimental results show that this method can provide accurate smooth closed boundary, precision can reach sub-pixel level. The recognition accuracy rate is high.