Effective and Adaptive Fingerprint Image Matching Using Contextual Filters
DOI:
https://doi.org/10.51983/ajcst-2013.2.2.1721Keywords:
Fingerprint image, Filtering, Fourier transform, image processing, Feature estimation, Quantization transformAbstract
This proposed method deals with several improvements to an adaptive fingerprint enhancement that is based on contextual filtering. The name adaptive denotes that the parameters are automatically adjusted based on the fingerprint image that is given as input. Five processing blocks are used in the adaptive fingerprint enhancement method. In the proposed system the four of these blocks are updated and this method is a novel. In this processing method the updated blocks are global analysis, matched filtering, local analysis and preprocessing. In the preprocessing and local analysis blocks the method simply used here are nonlinear dynamic range adjustment. Second, the process applies one or more forms of order statistical filters to the global analysis and matched filtering blocks. From this proposed method, these blocks produce a new improved adaptive fingerprint image processing techniques. These novel algorithm is appraised toward the NIST developed NBIS software for image recognition that is based on FVC databases.
References
L. Hong, Y. Wan, and A. Jain, “Fingerprint image enhancement Algorithm and performance evaluation,” IEEE Trans.volume. 20, no. 8, pp. 777–790, Aug. 1998.
D. Maio, D. Maltoni, S. Prabhakar , and A. K. Jain, Handbook of Fingerprint Recognition. 2nd edition. New York: Springer-Verlag, 2009.
L. O'Gorman and J. V. Nickerson, “Matched filter design for fingerprint image enhancement,” in Int. Conf. Acoust. Speech Signal Process., vol. 2. Apr. 1988, pp. 916–919.
K. Millard, B. G. Sherlock and D. M. Monro , “Fingerprint enhancement by directional Fourier filtering,” IEE Proc.-Vis., Image Signal Process., vol. 141, no. 2, pp. 87–94, Apr. 1994.
L. O'Gorman and J. Nickerson, “An approach to fingerprint filter design,” Pattern Recognit., vol. 22, no. 1, pp. 29–38, 1989.
B. J. Ström, N. Mikael, N. Jörgen, and C. Ingvar “Improved adaptive fingerprint binarization,” in Proc. IEEE Congr. Image Signal Process., May 2008, pp. 756–760.
H. Fronthaler, K. Kollreider, and J. Bigun, “Local feature for image enhancement and minutiae extraction in fingerprints,” IEEE Trans. Image Process., vol. 17, no. 3, pp. 354–363, Mar. 2008.
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2013 The Research Publication
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.