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Erschienen in:
2011 | OriginalPaper | Buchkapitel
Finger Knuckleprint Based Recognition System Using Feature Tracking
verfasst von : Aditya Nigam, Phalguni Gupta
Erschienen in: Biometric Recognition
Verlag: Springer Berlin Heidelberg
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This paper makes use of finger knuckleprints to propose an efficient biometrics system. Edge based local binary pattern (ELBP) is used to enhance the knuckleprint images. Highly distinctive texture patterns from the enhanced knuckleprint images are extracted for better classification. It has proposed a distance measure between two knuckleprint images. This system has been tested on the largest publicly available Hong Kong Polytechnic University (PolyU) finger knuckleprint database consisting 7920 knuckleprint images of 165 distinct subjects. It has achieved
CRR
of more than 99.1% for the top best match, in case of identification and
ERR
of 3.6%, in case of verification.