Abstract
A novel biometric defined as “knuckleprint” is presented in this paper. The Line feature of the knuckleprint with its distribution in the finger (which is defined as location feature) is extracted to identify a person. To enhance the performance of identification, hierarchical classification method is used to classify the location feature and line feature in different levels. Though this is the first attempt of knuckleprint identification, the accuracy rate reaches 96.88% on the database that contains 1,432 image samples, which testifies that knuckleprint is reliable as a biometric, and demonstrates the effectiveness and robustness of the features.
This work was supported by grant 2003RC069 from Research Foundation of Beijing Jiaotong University.
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© 2004 Springer-Verlag Berlin Heidelberg
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Li, Q., Qiu, Z., Sun, D., Wu, J. (2004). Personal Identification Using Knuckleprint. In: Li, S.Z., Lai, J., Tan, T., Feng, G., Wang, Y. (eds) Advances in Biometric Person Authentication. SINOBIOMETRICS 2004. Lecture Notes in Computer Science, vol 3338. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-30548-4_78
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DOI: https://doi.org/10.1007/978-3-540-30548-4_78
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-24029-7
Online ISBN: 978-3-540-30548-4
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