{"title":"基于鲁棒统计的图像比较新豪斯多夫距离","authors":"Oh-K. Kwon, D. Sim, Rae-Hong Park","doi":"10.1109/ICIP.1996.560359","DOIUrl":null,"url":null,"abstract":"A Hausdorff distance (HD) is one of commonly used measures for object matching. It calculates the distance between two point sets of edges in two-dimensional binary images without establishing correspondences. This paper analyzes the conventional HD measures based on robust statistics, and proposes robust HD measures based on M-estimation, least trimmed square (LTS), and /spl alpha/-trimmed mean methods. The matching performance by the conventional and proposed HD measures is compared with synthetic and real images.","PeriodicalId":192947,"journal":{"name":"Proceedings of 3rd IEEE International Conference on Image Processing","volume":"40 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1996-09-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"15","resultStr":"{\"title\":\"New Hausdorff distances based on robust statistics for comparing images\",\"authors\":\"Oh-K. Kwon, D. Sim, Rae-Hong Park\",\"doi\":\"10.1109/ICIP.1996.560359\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"A Hausdorff distance (HD) is one of commonly used measures for object matching. It calculates the distance between two point sets of edges in two-dimensional binary images without establishing correspondences. This paper analyzes the conventional HD measures based on robust statistics, and proposes robust HD measures based on M-estimation, least trimmed square (LTS), and /spl alpha/-trimmed mean methods. The matching performance by the conventional and proposed HD measures is compared with synthetic and real images.\",\"PeriodicalId\":192947,\"journal\":{\"name\":\"Proceedings of 3rd IEEE International Conference on Image Processing\",\"volume\":\"40 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1996-09-16\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"15\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of 3rd IEEE International Conference on Image Processing\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICIP.1996.560359\",\"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 of 3rd IEEE International Conference on Image Processing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICIP.1996.560359","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
New Hausdorff distances based on robust statistics for comparing images
A Hausdorff distance (HD) is one of commonly used measures for object matching. It calculates the distance between two point sets of edges in two-dimensional binary images without establishing correspondences. This paper analyzes the conventional HD measures based on robust statistics, and proposes robust HD measures based on M-estimation, least trimmed square (LTS), and /spl alpha/-trimmed mean methods. The matching performance by the conventional and proposed HD measures is compared with synthetic and real images.
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