Abstract
The problem of combining biometric matchers for person verification can be viewed as a pattern classification problem, and any trainable pattern classification algorithm can be used for score combination. But biometric matchers of different modalities possess a property of the statistical independence of their output scores. In this work we investigate if utilizing this independence knowledge results in the improvement of the combination algorithm. We show both theoretically and experimentally that utilizing independence provides better approximation of score density functions, and results in combination improvement.
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© 2006 Springer-Verlag Berlin Heidelberg
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Tulyakov, S., Govindaraju, V. (2006). Utilizing Independence of Multimodal Biometric Matchers. In: Gunsel, B., Jain, A.K., Tekalp, A.M., Sankur, B. (eds) Multimedia Content Representation, Classification and Security. MRCS 2006. Lecture Notes in Computer Science, vol 4105. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11848035_6
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DOI: https://doi.org/10.1007/11848035_6
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-39392-4
Online ISBN: 978-3-540-39393-1
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