A Novel Method of Fingerprint Classification Using Image Parameters on ANFIS

International Journal of Computer Theory and Engineering 10/2009; 1:370-375. DOI: 10.7763/IJCTE.2009.V1.55
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    ABSTRACT: Person identification systems based on fingerprint patterns called Automatic Fingerprint Identification Systems, AFIS, are some of the most widely used biometric methods since they provide a high degree of success. The accuracy of AFIS is mainly due to some unique characteristics called minutiae, which are points where a curve track finishes, intersects with another curve track, or branches off. During past decades several efficient minutia-based fingerprint recognition algorithms have been proposed which achieve false recognition rates close to 1%, however, their recognition rate may be still improved. To this end, this paper presents a fingerprint recognition method using a combination of the Fast Fourier Transform (FFT) with Gabor filters for image enhancement. Next, fingerprint recognition is carried out using a novel recognition stage based on Local Features and Hu invariant moments for verification.
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