Visible to the public Fingerprint Enhancement for Direct Grayscale Minutiae Extraction by Combining MFRAT and Gabor Filters

TitleFingerprint Enhancement for Direct Grayscale Minutiae Extraction by Combining MFRAT and Gabor Filters
Publication TypeConference Paper
Year of Publication2016
AuthorsVan, Hoang Thien, Van Vu, Giang, Le, Thai Hoang
Conference NameProceedings of the Seventh Symposium on Information and Communication Technology
PublisherACM
Conference LocationNew York, NY, USA
ISBN Number978-1-4503-4815-7
Keywordsadaptive filtering, adaptive MFRAT filter, complex filter, enhancement, fingerprints, Gabor filter, linear symmetry filter, pubcrawl, Resiliency, scalabilty
AbstractMinutiae 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).
URLhttp://doi.acm.org/10.1145/3011077.3011127
DOI10.1145/3011077.3011127
Citation Keyvan_fingerprint_2016