DocumentCode
2609616
Title
Pores and Ridges: Fingerprint Matching Using Level 3 Features
Author
Jain, Anil ; Chen, Yi ; Demirkus, Meltem
Author_Institution
Dept. of Comput. Sci. & Eng., Michigan State Univ.
Volume
4
fYear
0
fDate
0-0 0
Firstpage
477
Lastpage
480
Abstract
Fingerprint friction ridge details are generally described in a hierarchical order at three levels, namely, Level 1 (pattern), Level 2 (minutiae points) and Level 3 (pores and ridge shape). Although high resolution sensors (~1000 dpi) have become commercially available and have made it possible to reliably extract Level 3 features, most automated fingerprint identification systems (AFIS) employ only Level 1 and Level 2 features. As a result, increasing the scan resolution does not provide any matching performance improvement (1998). We develop a matcher that utilizes Level 3 features, including pores and ridge contours, for 1000 dpi fingerprint matching. Level 3 features are automatically extracted using wavelet transform and Gabor filters and are locally matched using the ICP algorithm. Our experiments on a median-sized database show that Level 3 features carry significant discriminatory information. EER values are reduced (relatively ~20%) when Level 3 features are employed in combination with Level 1 and 2 features
Keywords
Gabor filters; fingerprint identification; image matching; wavelet transforms; Gabor filters; automated fingerprint identification systems; fingerprint friction ridge details; fingerprint matching; high resolution sensor; wavelet transform; Data mining; Feature extraction; Fingerprint recognition; Friction; Gabor filters; Iterative closest point algorithm; Sensor phenomena and characterization; Sensor systems; Shape; Wavelet transforms;
fLanguage
English
Publisher
ieee
Conference_Titel
Pattern Recognition, 2006. ICPR 2006. 18th International Conference on
Conference_Location
Hong Kong
ISSN
1051-4651
Print_ISBN
0-7695-2521-0
Type
conf
DOI
10.1109/ICPR.2006.938
Filename
1699882
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