文件列表:

指纹识别_release30\19_7.bmp (66614, 2001-01-11)
指纹识别_release30\22443.bmp (132118, 2000-08-21)
指纹识别_release30\37_3.bmp (66614, 2001-01-11)
指纹识别_release30\37_5_2.bmp (66614, 2001-01-11)
指纹识别_release30\37_7.bmp (66614, 2001-01-11)
指纹识别_release30\centralizing.m (11549, 2004-06-23)
指纹识别_release30\conv2fft.m (6943, 2004-06-19)
指纹识别_release30\Cropping.m (1947, 2004-05-22)
指纹识别_release30\fprec.m (20312, 2004-06-28)
指纹识别_release30\gabor2d_sub.m (642, 2004-04-26)
指纹识别_release30\mirror.m (424, 2004-06-19)
指纹识别_release30\old_version.zip (298672, 2004-06-29)
指纹识别_release30\recrop.m (122, 2004-06-19)
指纹识别_release30\sector_norm.m (2773, 2004-04-26)
指纹识别_release30\vedicentro.m (499, 2004-06-19)
指纹识别_release30\whichsector.m (1203, 2004-04-26)
指纹识别_release30 (0, 2007-12-12)

Unzip all files into Matlab current directory and type "fprec" to start fingerprint image processing. Type "helpwin fprec" for more detailed informations. Notes: old_version.zip is the previous release (Fingerprint Recognition System 2.0) % Filterbank-Based Fingerprint Matching (A.K.Jain, S.Prabhakar, L.Hong and S.Pankanti, 2000) % % Abstract % With identity fraud in our society reaching unprecedented proportions and with an increasing emphasis on % the emerging automatic personal identification applications, biometrics-based verification, especially % fingerprint-based identification, is receiving a lot of attention. There are two major shortcomings % of the traditional approaches to fingerprint representation. For a considerable fraction of population, % the representations based on explicit detection of complete ridge structures in the fingerprint are % difficult to extract automatically. The widely used minutiae-based representation does not utilize a % significant component of the rich discriminatory information available in the fingerprints. Local ridge % structures cannot be completely characterized by minutiae. Further, minutiae-based matching has difficulty % in quickly matching two fingerprint images containing different number of unregistered minutiae points. % The proposed filter-based algorithm uses a bank of Gabor filters to capture both local and global details % in a fingerprint as a compact fixed length FingerCode. The fingerprint matching is based on the Euclidean % distance between the two corresponding FingerCodes and hence is extremely fast. We are able to achieve a % verification accuracy which is only marginally inferior to the best results of minutiae-based algorithms % published in the open literature. Our system performs better than a state-of-the-art minutiae-based system % when the performance requirement of the application system does not demand a very low false acceptance rate. % Finally, we show that the matching performance can be improved by combining the decisions of the matchers % based on complementary (minutiae-based and filter-based) fingerprint information. % % Index Terms: Biometrics, FingerCode, fingerprints, flow pattern, Gabor filters, matching, texture, verification. % % Type "fprec" on Matlab command window to start image processing. % This source code provides a new, improved GUI respect to the previous release. % Simulation parameters can be changed in this file: % % n_bands: the number of concentric bands % h_bands: the width of each band in pixels % n_arcs: the number of arcs (each band has exactly n_arcs arcs) % h_radius: the inner radius in pixel (the central band is not considered % because it is a too small area) % num_disk: the number of gabor filters % % n_sectors and h_lato rapresents respectively the total number of sectors % (the length of the feature vector associated to each filter of filter-bank: % there are num_disk gabor filters) and the height of the cropped image in pixels. % N_secors and h_lato should not be changed. % % % $Revision: 1.0 $ $Date: 2002.10.02 $ % $Revision: 2.0 $ $Date: 2003.11.29 $ % $Revision: 3.0 $ $Date: 2004.06.22 $ by Luigi Rosa % email: luigi.rosa@tiscali.it % mobile: +393403463208 % website: http://utenti.lycos.it/matlab % % % Modified respect to the previous version: % % - Major bugs fixed % - New GUI % - 8 Gabor filters 0 22.5 45 67.5 90 112.5 135 157.5 degree % - Convolution is performed in frequency domain % - DataBase % - Fingerprint matching % - Error management % - Complex filtering techniques % - Improved core point determination % - Robustness against noise % - Mo ... ...

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