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Proceedings Paper

Optimal correlation filter for fingerprint verification
Author(s): Danny Roberge; Colin Soutar; Bhagavatula Vijaya Kumar
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Paper Abstract

We present the derivation of an optimal correlation filter for fingerprint verification. The filter comprises multiple versions of the system user's fingerprint (i.e. it is a composite filter). Also, the characteristics of the filter can be adjusted so that its performance in a correlator is similar to that of a matched-filter or an inverse-filter, or some compromise between the two. It is these attributes that make this filter structure attractive for the task of fingerprint verification. The composite nature of the filter offers distortion tolerance by encompassing several different versions of the fingerprint image, while the tailored characteristics of the filters allows us to produce output correlation planes that can easily be processed. The filter was developed using a 'standard' database, with the objective of separating the two classes of input to the system: 'legitimate users' and 'attackers.' Specifically, the filter is optimized to minimize the probability of error (i.e. misclassification of user). Both the design and the implementation of the optimal fingerprint filter are covered in this paper.

Paper Details

Date Published: 23 March 1998
PDF: 11 pages
Proc. SPIE 3386, Optical Pattern Recognition IX, (23 March 1998); doi: 10.1117/12.304756
Show Author Affiliations
Danny Roberge, Mytec Technologies Inc. (Canada)
Colin Soutar, Mytec Technologies Inc. (Canada)
Bhagavatula Vijaya Kumar, Carnegie Mellon Univ. (United States)

Published in SPIE Proceedings Vol. 3386:
Optical Pattern Recognition IX
David P. Casasent; Tien-Hsin Chao, Editor(s)

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