10-04-2017, 09:08 PM
Presented By:
Shlomo Greenberg, Mayer Aladjem, Daniel Kogan and Itshak Dimitrov
Electrical and Computer Engineering Department,
Abstract
Extracting minutiae from fingerprint images is one of the most important steps in automatic fingerprint identification and classification. Minutiae are local discontinuities in the fingerprint pattern, mainly terminations and bifurcations. In this work we propose two methods for fingerprint image enhancement. The first one is carried out using local histogram equalization, Wiener filtering, and image binarization. The second method use a unique anisotropic filter for direct grayscale enhancement. The results achieved are compared with those obtained through some other methods. Both methods show some improvement in the minutiae detection process in terms of either efficiency or time required.
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http://fvs.sourceforgeC27_icpr2000.pdf
http://citeseerx.ist.psu.edu/viewdoc/dow...1&type=pdf
http://cubs.buffalo.edu/pdf/finger-stft.pdf