Fingerprint Recognition Using Gabor Filter And Frequency Domain Filtering

Abstract

Fingerprint recognition is one of the most popular methods used for identification with greater degree of success. The fingerprint has unique characteristics called minutiae, which are points where a curve track finishes, intersect or branches off. In this work a novel method for Fingerprint recognition is considered using a combination of Fast Fourier Transform (FFT) and Gabor Filters to enhancement the image. The proposed method involves combination of Gabor filter and Frequency domain filtering for enhancing the fingerprint. With eight different orientations of Gabor filter, features of the fingerprint are extracting and are combined. In Frequency domain filtering, the fingerprint image is subdivided into 32*32 small frames. Features are extracted from these frames in frequency domain. Final enhanced fingerprint is obtained the results of Gabor filter and frequency domain filtering. Binarization and Thinning follows next where the enhanced fingerprint is converted to binary and the ridges are thinned to one pixel width. This helps in extracting the Minutiae parts (ridge bifurcation and ridge endings). Euclidian distance method used for performance of recognition. The overall recognition rate for the proposed method is 95% obtained as which is much better compared to histogram method where the recognition rate is 64%. This project is implemented using MATLAB. Keywords - Gabor filter, fingerprint, FFT, Minutia, AFIS.