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Proceedings Paper

Adaptive fingerprint enhancement and identification using linear parametric models
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Paper Abstract

Historically, due to its uniqueness and immutability, fingerprints have been used as evidence in criminal cases and in security identification as well as authorization verification applications. In this research, adaptive linear DWT models are developed to describe the fingerprint features (DWT coefficients) to be identified. The proposed model can be used to enhance the fingerprint characteristics identified from fingerprint images to improve recognition. This adaptive model identification technique is then applied to degraded or incomplete fingerprint images to demonstrate the efficacy of the technique under non-ideal conditions. The performance of the method is then compared to previously published research by the authors on identification of degraded fingerprints using PCA-and ICA-based features.

Paper Details

Date Published: 15 September 2008
PDF: 12 pages
Proc. SPIE 7073, Applications of Digital Image Processing XXXI, 70731L (15 September 2008); doi: 10.1117/12.795799
Show Author Affiliations
Mehrübe Mehrübeoğlu, Texas A&M Univ., Corpus Christi (United States)
Lifford McLauchlan, Texas A&M Univ., Kingsville (United States)

Published in SPIE Proceedings Vol. 7073:
Applications of Digital Image Processing XXXI
Andrew G. Tescher, Editor(s)

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