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Optical Engineering

Optimal trade-off filter for the correlation of fingerprints
Author(s): Danny Roberge; Colin Soutar; Bhagavatula Vijaya Kumar
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Paper Abstract

We present the derivation of an optimal trade-off filter developed for the correlation of fingerprints. The filter is comprised of 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, an inverse filter, or some compromise between the two. These attributes 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 filter enables us to produce a filter that is a trade-off between this distortion tolerance and its discrimination capability. 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.

Paper Details

Date Published: 1 January 1999
PDF: 6 pages
Opt. Eng. 38(1) doi: 10.1117/1.602075
Published in: Optical Engineering Volume 38, Issue 1
Show Author Affiliations
Danny Roberge, Forensic Technology Inc. (Canada)
Colin Soutar, Mytec Technologies Inc. (Canada)
Bhagavatula Vijaya Kumar, Carnegie Mellon Univ. (United States)


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