Performance improvement in a fingerprint classification system using anisotropic diffusion
Resumen:
In a previous work, [1], we evaluated a classification algorithm based on the Karu-Jain method [2] and compared the performance with a fully manual method used at the Dirección Nacional de Identificación Civil (DNIC). In this paper, we analyze the high performance improvement achieved using anisotropic diffusion instead of pure averaging for the directions smoothing. We also define a quality measure that shows high correlation with the experts’ criteria. The results are evaluated over 2800 images extracted from a 4 million fingerprint card archive maintained by DNIC.
| 2004 | |
| PROCESAMIENTO de SEÑALES | |
| Inglés | |
| Universidad de la República | |
| COLIBRI | |
| https://hdl.handle.net/20.500.12008/21149 | |
| Acceso abierto | |
| Licencia Creative Commons Atribución – No Comercial – Sin Derivadas (CC - By-NC-ND) |
| _version_ | 1807522893014237184 |
|---|---|
| author | Pardo, Alvaro |
| author2 | Fernández, Alicia Gómez, Alvaro Barattini, Jose Gianarelli, Gustavo Vallarino, Gonzalo |
| author2_role | author author author author author |
| author_facet | Pardo, Alvaro Fernández, Alicia Gómez, Alvaro Barattini, Jose Gianarelli, Gustavo Vallarino, Gonzalo |
| author_role | author |
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| collection | COLIBRI |
| dc.creator.none.fl_str_mv | Pardo, Alvaro Fernández, Alicia Gómez, Alvaro Barattini, Jose Gianarelli, Gustavo Vallarino, Gonzalo |
| dc.date.accessioned.none.fl_str_mv | 2019-07-03T16:35:44Z |
| dc.date.available.none.fl_str_mv | 2019-07-03T16:35:44Z |
| dc.date.issued.es.fl_str_mv | 2004 |
| dc.date.submitted.es.fl_str_mv | 20190703 |
| dc.description.abstract.none.fl_txt_mv | In a previous work, [1], we evaluated a classification algorithm based on the Karu-Jain method [2] and compared the performance with a fully manual method used at the Dirección Nacional de Identificación Civil (DNIC). In this paper, we analyze the high performance improvement achieved using anisotropic diffusion instead of pure averaging for the directions smoothing. We also define a quality measure that shows high correlation with the experts’ criteria. The results are evaluated over 2800 images extracted from a 4 million fingerprint card archive maintained by DNIC. |
| dc.description.es.fl_txt_mv | Trabajo presentado en CIARP 2004: Progress in Pattern Recognition, Image Analysis and Applications, 2004 |
| dc.identifier.citation.es.fl_str_mv | Pardo, A., Fernández, A., Gómez, A., Barattini, J, Gianarelli, G, Vallarino, G. Performance improvement in a fingerprint classification system using anisotropic diffusion [Preprint] Publicado en Proceedings of the CIARP 2004: Progress in Pattern Recognition, Image Analysis and Applications, 2004 https://doi.org/10.1007/978-3-540-30463-0_73 |
| dc.identifier.uri.none.fl_str_mv | https://hdl.handle.net/20.500.12008/21149 |
| dc.language.iso.none.fl_str_mv | en eng |
| dc.rights.license.none.fl_str_mv | Licencia Creative Commons Atribución – No Comercial – Sin Derivadas (CC - By-NC-ND) |
| dc.rights.none.fl_str_mv | info:eu-repo/semantics/openAccess |
| dc.source.none.fl_str_mv | reponame:COLIBRI instname:Universidad de la República instacron:Universidad de la República |
| dc.subject.other.es.fl_str_mv | PROCESAMIENTO de SEÑALES |
| dc.title.none.fl_str_mv | Performance improvement in a fingerprint classification system using anisotropic diffusion |
| dc.type.es.fl_str_mv | Preprint |
| dc.type.none.fl_str_mv | info:eu-repo/semantics/preprint |
| dc.type.version.none.fl_str_mv | info:eu-repo/semantics/submittedVersion |
| description | Trabajo presentado en CIARP 2004: Progress in Pattern Recognition, Image Analysis and Applications, 2004 |
| eu_rights_str_mv | openAccess |
| format | preprint |
| id | COLIBRI_023781962970ae9f758eaee0fd7ef750 |
| identifier_str_mv | Pardo, A., Fernández, A., Gómez, A., Barattini, J, Gianarelli, G, Vallarino, G. Performance improvement in a fingerprint classification system using anisotropic diffusion [Preprint] Publicado en Proceedings of the CIARP 2004: Progress in Pattern Recognition, Image Analysis and Applications, 2004 https://doi.org/10.1007/978-3-540-30463-0_73 |
| instacron_str | Universidad de la República |
| institution | Universidad de la República |
| instname_str | Universidad de la República |
| language | eng |
| language_invalid_str_mv | en |
| network_acronym_str | COLIBRI |
| network_name_str | COLIBRI |
| oai_identifier_str | oai:colibri.udelar.edu.uy:20.500.12008/21149 |
| publishDate | 2004 |
| reponame_str | COLIBRI |
| repository.mail.fl_str_mv | mabel.seroubian@seciu.edu.uy |
| repository.name.fl_str_mv | COLIBRI - Universidad de la República |
| repository_id_str | 4771 |
| rights_invalid_str_mv | Licencia Creative Commons Atribución – No Comercial – Sin Derivadas (CC - By-NC-ND) |
| spelling | 2019-07-03T16:35:44Z2019-07-03T16:35:44Z200420190703Pardo, A., Fernández, A., Gómez, A., Barattini, J, Gianarelli, G, Vallarino, G. Performance improvement in a fingerprint classification system using anisotropic diffusion [Preprint] Publicado en Proceedings of the CIARP 2004: Progress in Pattern Recognition, Image Analysis and Applications, 2004 https://doi.org/10.1007/978-3-540-30463-0_73https://hdl.handle.net/20.500.12008/21149Trabajo presentado en CIARP 2004: Progress in Pattern Recognition, Image Analysis and Applications, 2004In a previous work, [1], we evaluated a classification algorithm based on the Karu-Jain method [2] and compared the performance with a fully manual method used at the Dirección Nacional de Identificación Civil (DNIC). In this paper, we analyze the high performance improvement achieved using anisotropic diffusion instead of pure averaging for the directions smoothing. We also define a quality measure that shows high correlation with the experts’ criteria. The results are evaluated over 2800 images extracted from a 4 million fingerprint card archive maintained by DNIC.Made available in DSpace on 2019-07-03T16:35:44Z (GMT). No. of bitstreams: 5 VGBGFP04.pdf: 317386 bytes, checksum: 916499cbfbe3c3d44b8c0394d4b44395 (MD5) license_text: 0 bytes, checksum: d41d8cd98f00b204e9800998ecf8427e (MD5) license_url: 49 bytes, checksum: 4afdbb8c545fd630ea7db775da747b2f (MD5) license_rdf: 0 bytes, checksum: d41d8cd98f00b204e9800998ecf8427e (MD5) license.txt: 4267 bytes, checksum: 6429389a7df7277b72b7924fdc7d47a9 (MD5) Previous issue date: 2004enengLas obras depositadas en el Repositorio se rigen por la Ordenanza de los Derechos de la Propiedad Intelectual de la Universidad De La República. (Res. Nº 91 de C.D.C. de 8/III/1994 – D.O. 7/IV/1994) y por la Ordenanza del Repositorio Abierto de la Universidad de la República (Res. Nº 16 de C.D.C. de 07/10/2014)info:eu-repo/semantics/openAccessLicencia Creative Commons Atribución – No Comercial – Sin Derivadas (CC - By-NC-ND)PROCESAMIENTO de SEÑALESPerformance improvement in a fingerprint classification system using anisotropic diffusionPreprintinfo:eu-repo/semantics/preprintinfo:eu-repo/semantics/submittedVersionreponame:COLIBRIinstname:Universidad de la Repúblicainstacron:Universidad de la RepúblicaPardo, AlvaroFernández, AliciaGómez, AlvaroBarattini, JoseGianarelli, GustavoVallarino, GonzaloProcesamiento de SeñalesTratamiento de 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- Universidad de la Repúblicafalse |
| spellingShingle | Performance improvement in a fingerprint classification system using anisotropic diffusion Pardo, Alvaro PROCESAMIENTO de SEÑALES |
| status_str | submittedVersion |
| title | Performance improvement in a fingerprint classification system using anisotropic diffusion |
| title_full | Performance improvement in a fingerprint classification system using anisotropic diffusion |
| title_fullStr | Performance improvement in a fingerprint classification system using anisotropic diffusion |
| title_full_unstemmed | Performance improvement in a fingerprint classification system using anisotropic diffusion |
| title_short | Performance improvement in a fingerprint classification system using anisotropic diffusion |
| title_sort | Performance improvement in a fingerprint classification system using anisotropic diffusion |
| topic | PROCESAMIENTO de SEÑALES |
| url | https://hdl.handle.net/20.500.12008/21149 |
