{"title":"带小波的高效C-V模型","authors":"Jifei Liu, L. Min","doi":"10.1109/IHMSC.2012.48","DOIUrl":null,"url":null,"abstract":"We propose an efficient C-V model with wavelet transform to speed up the C-V model evolution. Firstly, the image is decomposed into the downsizing and approximation sub-image with wavelet transform. Then the sub-image composed with the approximation wavelet coefficient matrix is pre-segmented using C-V model to get an approximation curve in a short time. Thirdly, in order to get a fine segmentation, the original image is segmented subtly using C-V model again, of which the initial curve is reconstructed by the result of pre-segmentation. The experimental results validate the effectiveness and feasibility of this model.","PeriodicalId":431532,"journal":{"name":"2012 4th International Conference on Intelligent Human-Machine Systems and Cybernetics","volume":"14 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2012-08-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"An Efficient C-V Model with Wavelets\",\"authors\":\"Jifei Liu, L. Min\",\"doi\":\"10.1109/IHMSC.2012.48\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"We propose an efficient C-V model with wavelet transform to speed up the C-V model evolution. Firstly, the image is decomposed into the downsizing and approximation sub-image with wavelet transform. Then the sub-image composed with the approximation wavelet coefficient matrix is pre-segmented using C-V model to get an approximation curve in a short time. Thirdly, in order to get a fine segmentation, the original image is segmented subtly using C-V model again, of which the initial curve is reconstructed by the result of pre-segmentation. The experimental results validate the effectiveness and feasibility of this model.\",\"PeriodicalId\":431532,\"journal\":{\"name\":\"2012 4th International Conference on Intelligent Human-Machine Systems and Cybernetics\",\"volume\":\"14 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2012-08-26\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2012 4th International Conference on Intelligent Human-Machine Systems and Cybernetics\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/IHMSC.2012.48\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2012 4th International Conference on Intelligent Human-Machine Systems and Cybernetics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IHMSC.2012.48","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
We propose an efficient C-V model with wavelet transform to speed up the C-V model evolution. Firstly, the image is decomposed into the downsizing and approximation sub-image with wavelet transform. Then the sub-image composed with the approximation wavelet coefficient matrix is pre-segmented using C-V model to get an approximation curve in a short time. Thirdly, in order to get a fine segmentation, the original image is segmented subtly using C-V model again, of which the initial curve is reconstructed by the result of pre-segmentation. The experimental results validate the effectiveness and feasibility of this model.