Fingerprint data acquisition, desmearing, wavelet feature extraction, and identification

Harold H. Szu; Charles C. Hsu; Joseph P. Garcia; Brian A. Telfer

doi:10.1117/12.205376

6 April 1995 Fingerprint data acquisition, desmearing, wavelet feature extraction, and identification

Harold H. Szu, Charles C. Hsu, Joseph P. Garcia, Brian A. Telfer

Proceedings Volume 2491, Wavelet Applications II; (1995) https://doi.org/10.1117/12.205376
Event: SPIE's 1995 Symposium on OE/Aerospace Sensing and Dual Use Photonics, 1995, Orlando, FL, United States

Abstract

In this paper, we present (1) a design concept of a fingerprint scanning system that can reject severely blurred inputs for retakes and then de-smear those less blurred prints. The de-smear algorithm is new and is based on the digital filter theory of the lossless QMF (quadrature mirror filter) subband coding. Then, we present (2) a new fingerprint minutia feature extraction methodology which uses a 2D STAR mother wavelet that can efficiently locate the fork feature anywhere on the fingerprints in parallel and is independent of its scale, shift, and rotation. Such a combined system can achieve high data compression to send through a binary facsimile machine that when combined with a tabletop computer can achieve the automatic finger identification systems (AFIS) using today's technology in the office environment. An interim recommendation for the National Crime Information Center is given about how to reduce the crime rate by an upgrade of today's police office technology in the light of the military expertise in ATR.

Citation Download Citation

Harold H. Szu, Charles C. Hsu, Joseph P. Garcia, and Brian A. Telfer "Fingerprint data acquisition, desmearing, wavelet feature extraction, and identification", Proc. SPIE 2491, Wavelet Applications II, (6 April 1995); https://doi.org/10.1117/12.205376

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