{"title":"基于局部描述符的指纹骨架匹配","authors":"Julien Bohné, V. Despiegel","doi":"10.1109/BTAS.2009.5339032","DOIUrl":null,"url":null,"abstract":"In this paper, we present a new fingerprint matching algorithm based on a local skeleton descriptor. This descriptor uses ridge count information to encode minutiae locations in a small neighborhood. Taking advantage of ridge count properties, our descriptor is robust to distortions. We developed an efficient algorithm to match our descriptor and a strategy to combine matchings of many local descriptors. Our algorithm obtains interesting results on both tenprint-to-tenprint and latent-to-tenprint matchings.","PeriodicalId":325900,"journal":{"name":"2009 IEEE 3rd International Conference on Biometrics: Theory, Applications, and Systems","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2009-09-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":"{\"title\":\"Fingerprint skeleton matching based on local descriptor\",\"authors\":\"Julien Bohné, V. Despiegel\",\"doi\":\"10.1109/BTAS.2009.5339032\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper, we present a new fingerprint matching algorithm based on a local skeleton descriptor. This descriptor uses ridge count information to encode minutiae locations in a small neighborhood. Taking advantage of ridge count properties, our descriptor is robust to distortions. We developed an efficient algorithm to match our descriptor and a strategy to combine matchings of many local descriptors. Our algorithm obtains interesting results on both tenprint-to-tenprint and latent-to-tenprint matchings.\",\"PeriodicalId\":325900,\"journal\":{\"name\":\"2009 IEEE 3rd International Conference on Biometrics: Theory, Applications, and Systems\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2009-09-28\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"4\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2009 IEEE 3rd International Conference on Biometrics: Theory, Applications, and Systems\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/BTAS.2009.5339032\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2009 IEEE 3rd International Conference on Biometrics: Theory, Applications, and Systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/BTAS.2009.5339032","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Fingerprint skeleton matching based on local descriptor
In this paper, we present a new fingerprint matching algorithm based on a local skeleton descriptor. This descriptor uses ridge count information to encode minutiae locations in a small neighborhood. Taking advantage of ridge count properties, our descriptor is robust to distortions. We developed an efficient algorithm to match our descriptor and a strategy to combine matchings of many local descriptors. Our algorithm obtains interesting results on both tenprint-to-tenprint and latent-to-tenprint matchings.