Department of Electronic Engineering, Faculty of Electrical and Computer Engineering, University of Birjand
Abstract
Identification and Verification using fingerprint has direct relation with quality of fingerprint. In this paper, novel method is proposed to enhance the quality of fingerprint using Arc-Gabor filter bank. Indeed proposed filter bank is an adaptive version of standard filter bank for fingerprint. Evaluating the ability of proposed method is done using two methods. In the first method, results of verification and identification using normalized histogram of Binarized Statistical Image Feature (BSIF) are compared for the fingerprints before and after using proposed method. And in the second method, Peak Signal to Noise Ratio (PSNR) is used. Two databases DBI and DBII are used for evaluation. Using proposed method, for verification Equal Error Rate, are decrease from (15.89% and 11.70%) to (11.35% and 8.00%), respectively, and for identification, 1st rank correct recognition rate are increased from (69.28% and 71.16%) to (78.80% and 81.70%), respectively. Average values of PSNR for enhanced fingerprint using proposed methods are more than other version of Gabor filter.
Taghipour-Gorjikolaie, M., Razavi, S. M., & Mehrshad, N. (2016). Finger Print Enhancement using Arc_Gabor Filter-bank. Journal of Machine Vision and Image Processing, 3(1), 1-17.
MLA
Mehran Taghipour-Gorjikolaie; Seyyed Mohammad Razavi; Naser Mehrshad. "Finger Print Enhancement using Arc_Gabor Filter-bank". Journal of Machine Vision and Image Processing, 3, 1, 2016, 1-17.
HARVARD
Taghipour-Gorjikolaie, M., Razavi, S. M., Mehrshad, N. (2016). 'Finger Print Enhancement using Arc_Gabor Filter-bank', Journal of Machine Vision and Image Processing, 3(1), pp. 1-17.
VANCOUVER
Taghipour-Gorjikolaie, M., Razavi, S. M., Mehrshad, N. Finger Print Enhancement using Arc_Gabor Filter-bank. Journal of Machine Vision and Image Processing, 2016; 3(1): 1-17.
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