NDLI: Towards integrating level-3 Features with perspiration pattern for robust fingerprint recognition

Content Provider	IEEE Xplore Digital Library
Author	Abhyankar, A. Schuckers, S.
Copyright Year	2010
Description	Author affiliation: Electrical and Computer Eng Dept., Clarkson University, Potsdam, NY, USA (Abhyankar, A.; Schuckers, S.)
Abstract	Level-3 fingerprint features from fingerprint images like pores are difficult to capture detect, and involve high resolution scanners with higher ppi count. However, these features provide finer information about a fingerprint characteristics. Furthermore, fingerprint pores may be useful in determining liveness of fingerprint in order to prevent spoofing of fingerprint devices. In this study fingerprint pores along the ridges are used for fingerprint matching. Wavelet based fingerprint enhancement techniques are implemented to ease detection of the level-3 features. Delaunay triangulation based alignment and matching of the fingerprints is performed. The pores are checked for the liveness by perspiration activity in the time series captures. The developed matching scheme is tested for the high resolution data (686 ppi) for 114 live and spoof fingerprint classes. ROC is plotted and EER of 2.97% is obtained.
Starting Page	3085
Ending Page	3088
File Size	1309106
Page Count	4
File Format	PDF
ISBN	9781424479924
ISSN	15224880
e-ISBN	9781424479948
e-ISBN	9781424479931
DOI	10.1109/ICIP.2010.5654261
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2010-09-26
Publisher Place	Hong Kong
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Feature extraction Image edge detection Fingerprint recognition Wavelet transforms Image resolution Wavelet analysis Wavelet domain wavelets fingerprints level-3 features pores perspiration pattern liveness
Content Type	Text
Resource Type	Article

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