Abstract
This paper aims to study the accuracy and robustness of personal identification or verification systems where palmprint is the only modality available or utilized. Three different representations of palmprint are fused at the score-level by the sum rule, and at the decision-level by weighed or majority votes. Results showed that fusion at the score-level is easier to formulate and justify, and performs better than fusing at the decision-level. On a database of 340 subjects (10 samples/class), 10-fold and 2-fold cross-validation is accurate to 99.8% and 99.2% respectively. When operating as a verification system, it can achieve a false acceptance rate of 0.68% while maintaining a false rejection rate of 5%.
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Poon, C., Wong, D.C.M., Shen, H.C. (2004). Personal Identification and Verification: Fusion of Palmprint Representations. In: Zhang, D., Jain, A.K. (eds) Biometric Authentication. ICBA 2004. Lecture Notes in Computer Science, vol 3072. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-25948-0_106
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DOI: https://doi.org/10.1007/978-3-540-25948-0_106
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-22146-3
Online ISBN: 978-3-540-25948-0
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