{"title":"利用翻译下的豪斯多夫距离对图像进行比较","authors":"D. Huttenlocher, W. Rucklidge, G. A. Klanderman","doi":"10.1109/CVPR.1992.223209","DOIUrl":null,"url":null,"abstract":"Efficient algorithms are provided for computing the Hausdorff distance between a binary image and all possible relative positions (translations) of a model, or a portion of that model. The computation is in many ways similar to binary correlation. However, it is more tolerant of perturbations in the locations of points because it measures proximity rather than exact superposition.<<ETX>>","PeriodicalId":325476,"journal":{"name":"Proceedings 1992 IEEE Computer Society Conference on Computer Vision and Pattern Recognition","volume":"130 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1992-06-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"102","resultStr":"{\"title\":\"Comparing images using the Hausdorff distance under translation\",\"authors\":\"D. Huttenlocher, W. Rucklidge, G. A. Klanderman\",\"doi\":\"10.1109/CVPR.1992.223209\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Efficient algorithms are provided for computing the Hausdorff distance between a binary image and all possible relative positions (translations) of a model, or a portion of that model. The computation is in many ways similar to binary correlation. However, it is more tolerant of perturbations in the locations of points because it measures proximity rather than exact superposition.<<ETX>>\",\"PeriodicalId\":325476,\"journal\":{\"name\":\"Proceedings 1992 IEEE Computer Society Conference on Computer Vision and Pattern Recognition\",\"volume\":\"130 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1992-06-15\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"102\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings 1992 IEEE Computer Society Conference on Computer Vision and Pattern Recognition\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CVPR.1992.223209\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings 1992 IEEE Computer Society Conference on Computer Vision and Pattern Recognition","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CVPR.1992.223209","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Comparing images using the Hausdorff distance under translation
Efficient algorithms are provided for computing the Hausdorff distance between a binary image and all possible relative positions (translations) of a model, or a portion of that model. The computation is in many ways similar to binary correlation. However, it is more tolerant of perturbations in the locations of points because it measures proximity rather than exact superposition.<>
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