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Fast Fingerprint Alignment Method and Weighted Feature Vector Extraction Method in Filterbank-Based Fingerprint Matching  

정석재 (아주대학교 정보통신연구소)
김동윤 (아주대학교 정보 및 컴퓨터공학부)
Publication Information
Journal of KIISE:Software and Applications / v.31, no.1, 2004 , pp. 71-81 More about this Journal
Abstract
Minutiae-based fingerprint identification systems use minutiae points, which cannot completely characterize local ridge structures. Further, this method requires many methods for matching two fingerprint images containing different number of minutiae points. Therefore, to represent the fired length information for one fingerprint image, the filterbank-based method was proposed as an alternative to minutiae-based fingerprint representation. However, it has two shortcomings. One shortcoming is that similar feature vectors are extracted from the different fingerprints which have the same fingerprint type. Another shortcoming is that this method has overload to reduce the rotation error in the fingerprint image acquisition. In this paper, we propose the minutia-weighted feature vector extraction method that gives more weight in extracting feature value, if the region has minutiae points. Also, we Propose new fingerprint alignment method that uses the average local orientations around the reference point. These methods improve the fingerprint system's Performance and speed, respectively. Experimental results indicate that the proposed methods can reduce the FRR of the filterbank-based fingerprint matcher by approximately 0.524% at a FAR of 0.967%, and improve the matching performance by 5% in ERR. The system speed is over 1.28 times faster.
Keywords
Biometric Authentication; Fingerprint Identification; Gabor Filter; Fingerprint Alignment; Filterbank-based Fingerprint Identification;
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Times Cited By KSCI : 1  (Citation Analysis)
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