15 September 2008 Adaptive fingerprint enhancement and identification using linear parametric models
Author Affiliations +
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.
© (2008) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Mehrübe Mehrübeoğlu, Mehrübe Mehrübeoğlu, Lifford McLauchlan, Lifford McLauchlan, } "Adaptive fingerprint enhancement and identification using linear parametric models", Proc. SPIE 7073, Applications of Digital Image Processing XXXI, 70731L (15 September 2008); doi: 10.1117/12.795799; https://doi.org/10.1117/12.795799


Improved method for extraction of fingerprint features
Proceedings of SPIE (July 31 2002)
Gabor wavelets for texture edge extraction
Proceedings of SPIE (August 17 1994)
Fractal-based watermarking of color images
Proceedings of SPIE (September 08 2011)
Unsupervised Segmentation Of Texture Images
Proceedings of SPIE (October 25 1988)

Back to Top