Fingerprint enhancement for direct grayscale minutiae extraction by combining MFRAT and Gabor filters

Minutiae are important features in the fingerprints matching. The effective of minutiae extraction depends greatly on the results of fingerprint enhancement. This paper proposes a novel fingerprint enhancement method for direct gray scale extracting minutiae based on combining Gabor filters with the Adaptive Modified Finite Radon Transform (AMFRAT) filters. First, the proposed method uses Gabor filters as band-pass filters for deleting the noise and clarifying ridges. Next, AMFRAT filters are applied for connecting broken ridges together, filling the created holes and clarifying linear symmetry of ridges quickly. AMFRAT is the MFRAT filter, the window size of which is adaptively adjusted according to the coherence values. The small window size is for high curvature ridge areas (small coherence value), and vice versa. As the result, the ridges are the linear symmetry areas, and more suitable for direct gray scale minutiae extraction. Finally, linear symmetry filter is only used for locating minutiae in an inverse model, as "lack of linear symmetry" occurs at minutiae points. Experimental results on FVC2004 databases DB4 (set A) shows that the proposed method is capable of improving the goodness index (GI).