Abstract
This paper presents a Dempster Shafer theory based classifier fusion algorithm to improve the performance of fingerprint verification. The proposed fusion algorithm combines decision induced match scores of minutiae, ridge, fingercode and pore based fingerprint verification algorithms and provides an improvement of at least 8.1% in the verification accuracy compared to the individual algorithms. Further, proposed fusion algorithm outperforms by at least 2.52% when compared with existing fusion algorithms. We also found that the use of Dempster’s rule of conditioning reduces the training time by approximately 191 seconds.
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© 2006 Springer-Verlag Berlin Heidelberg
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Singh, R., Vatsa, M., Noore, A., Singh, S.K. (2006). Dempster-Shafer Theory Based Classifier Fusion for Improved Fingerprint Verification Performance. In: Kalra, P.K., Peleg, S. (eds) Computer Vision, Graphics and Image Processing. Lecture Notes in Computer Science, vol 4338. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11949619_84
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DOI: https://doi.org/10.1007/11949619_84
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-68301-8
Online ISBN: 978-3-540-68302-5
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