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Titlebook: Automatic Fingerprint Recognition Systems; Nalini Ratha,Ruud Bolle Book 2004 Springer Science+Business Media New York 2004 algorithms.biom

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Unconstrained Global Optimization,ch in some countries prohibits the diffusion of such personal information. This chapter describes the SFINGE (acronym for Synthetic FINgerprint GEnerator) approach, developed by the BIOLAB team, which can be used to create, at zero cost, large fingerprint databases. The synthesis of each master fing
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History of Fingerprint Pattern Recognition,print classification systems of Vucetich and Henry in the 1890s through the advent of automated fingerprint identification. By chronicling the history of “manual” systems for recording storing, matching, and retrieving fingerprints, the article puts advances in automatic fingerprint recognition in h
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Fingerprint Quality Assessment, acquisition from each individual should provide useful information for personal identity verification or recognition. In other words, everybody should have the biometrics and it should be easy to sample or acquire. In practice, adverse signal acquisition conditions and inconsistent presentations of
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Image Filter Design for Fingerprint Enhancement,ency filter corresponding to ridge frequencies and a direction filter corresponding to ridge directions on the basis of fingerprint ridge characteristics. An energy function for selecting image features (i.e., frequencies and directions) is defined by power of images obtained with the above filters
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