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Published Articles >> Table of Contents >> Abstract
18th International Conference on Pattern Recognition (ICPR'06) Volume 4
pp. 473-476
Quality-based Score Level Fusion in Multibiometric Systems
Karthik Nandakumar, Michigan State University
Yi Chen, Michigan State University
Anil K. Jain, Michigan State University
Sarat C. Dass, Michigan State University
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DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/ICPR.2006.951
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| Abstract |
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The quality of biometric samples has a significant impact
on the accuracy of a matcher. Poor quality biometric
samples often lead to incorrect matching results because
the features extracted from these samples are not reliable.
Therefore, dynamically assigning weights to the outputs of
individual matchers based on the quality of the samples presented
at the input of the matchers can improve the overall
recognition performance of a multibiometric system. We
propose a likelihood ratio-based fusion scheme that takes
into account the quality of the biometric samples while combining
the match scores provided by the matchers. Instead
of estimating the quality of the template and query images
individually, we estimate a single quality metric for each
template-query pair based on the local image quality measures.
Experiments on a database of 320 users with iris and
fingerprint modalities demonstrate the advantages of utilizing
the quality information in multibiometric systems.
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 Additional Information
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Citation:
Karthik Nandakumar, Yi Chen, Anil K. Jain, Sarat C. Dass,
"Quality-based Score Level Fusion in Multibiometric Systems,"
icpr,
pp. 473-476,
18th International Conference on Pattern Recognition (ICPR'06) Volume 4,
2006
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