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Please use this identifier to cite or link to this item: http://hdl.handle.net/UCSP/15903
Title: Novel approaches for exclusive and continuous fingerprint classification
Authors: Montoya Zegarra, Javier
Paulo Papa, Joao
Leite, Neucimar
da Silva Torres, Ricardo
Falcao, Alexandre
Keywords: Classification rates;Continuous approaches;Data sets;Fingerprint authentications;Fingerprint classifications;Fingerprint images;Fingerprint matching;Forest classifiers;Multi class;Multi-resolution decompositions;Recognition methods;Similarity measures;Texture images;Object recognition
Issue Date: 2009
metadata.dc.relation.uri: https://www.scopus.com/inward/record.uri?eid=2-s2.0-60149091375&doi=10.1007%2f978-3-540-92957-4_34&partnerID=40&md5=0a16a4ca731f1a9b2d6e4768f46c057e
Abstract: This paper proposes novel exclusive and continuous approaches to guide the search and the retrieval in fingerprint image databases. Both approaches are useful to perform a coarse level classification of fingerprint images before fingerprint authentication tasks. Our approaches are characterized by: (1) texture image descriptors based on pairs of multi-resolution decomposition methods that encode effectively global and local fingerprint information, with similarity measures used for fingerprint matching purposes, and (2) a novel multi-class object recognition method based on the Optimum Path Forest classifier. Experiments were carried out on the standard NIST-4 dataset aiming to study the discriminative and scalability capabilities of our approaches. The high classification rates allow us demonstrate the feasibility and validity of our approaches for characterizing fingerprint images accurately. © 2009 Springer Berlin Heidelberg.
URI: http://repositorio.ucsp.edu.pe/handle/UCSP/15903
ISSN: 3029743
Appears in Collections:Artículos de investigación

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