Fingerprint Verification: A Fingerprint Verification Algorithm Using the Smallest Minimum Sum of Closest Euclidean Distance - Softcover
Inhaltsangabe
In this book, a Euclidean distance based minutia matching algorithm is proposed to improve the matching accuracy in fingerprint verification system. This algorithm extracts matched minutia pairs from input and template fingerprints by using the smallest minimum sum of closest Euclidean distance (SMSCED), corresponding rotation angle and empirically chosen statistical threshold values. Instead of using the minutia type and orientation angle, which are widely employed in existing algorithms, the proposed algorithm uses only the minutia location, to reduce the effect of non-linear distortion. Experimental results show that the proposed method has higher accuracy with improved verification rate and rejection rate.
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Reseña del editor
In this book, a Euclidean distance based minutia matching algorithm is proposed to improve the matching accuracy in fingerprint verification system. This algorithm extracts matched minutia pairs from input and template fingerprints by using the smallest minimum sum of closest Euclidean distance (SMSCED), corresponding rotation angle and empirically chosen statistical threshold values. Instead of using the minutia type and orientation angle, which are widely employed in existing algorithms, the proposed algorithm uses only the minutia location, to reduce the effect of non-linear distortion. Experimental results show that the proposed method has higher accuracy with improved verification rate and rejection rate.
Biografía del autor
Ujjal Kumar Bhowmik received his Master of Science in the Department of Electrical and Computer engineering to The School of Graduate Studies at The University of Alabama in Huntsville in the year of 2009
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Fingerprint Verification
Verlag:
LAP LAMBERT Academic Publishing Okt 2009, 2009
ISBN 10: 3838318714
ISBN 13: 9783838318714
Neu
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Taschenbuch. Zustand: Neu. Neuware -In this book, a Euclidean distance based minutia matching algorithm is proposed to improve the matching accuracy in fingerprint verification system. This algorithm extracts matched minutia pairs from input and template fingerprints by using the smallest minimum sum of closest Euclidean distance (SMSCED), corresponding rotation angle and empirically chosen statistical threshold values. Instead of using the minutia type and orientation angle, which are widely employed in existing algorithms, the proposed algorithm uses only the minutia location, to reduce the effect of non-linear distortion. Experimental results show that the proposed method has higher accuracy with improved verification rate and rejection rate.Books on Demand GmbH, Überseering 33, 22297 Hamburg 76 pp. Englisch. Artikel-Nr. 9783838318714
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