Novel Approaches for Exclusive and Continuous Fingerprint Classification

Authors:
Javier A. Montoya-Zegarra;João P. Papa;Neucimar J. Leite;Ricardo Silva Torres;Alexandre X. Falcão
Affiliations:
Computer Engineering Department, Faculty of Engineering, San Pablo Catholic University, Vallecito, Peru and Institute of Computing, State University of Campinas, São Paulo, Brazil;Institute of Computing, State University of Campinas, São Paulo, Brazil;Institute of Computing, State University of Campinas, São Paulo, Brazil;Institute of Computing, State University of Campinas, São Paulo, Brazil;Institute of Computing, State University of Campinas, São Paulo, Brazil
Venue:
PSIVT '09 Proceedings of the 3rd Pacific Rim Symposium on Advances in Image and Video Technology
Year:
2009

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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.