Abstract
To improve the efficiency of finger-vein recognition system over a large database, this paper proposed a level-based framework for automatically categorizing finger-vein images. The proposed framework consists of two layers. The first is based on appearance features, and the second is based on content features. In each layer, an improved k-means algorithm is employed for clustering finger-vein images. Finally,the POC (Phase-Only-Correction) algorithm is applied for image matching. Experimental results demonstrate that the proposed method exhibits an exciting performance in recognition efficiency improvement.
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Tan, D., Yang, J., Xu, C. (2013). Categorizing Finger-Vein Images Using a Hierarchal Approach. In: Sun, Z., Shan, S., Yang, G., Zhou, J., Wang, Y., Yin, Y. (eds) Biometric Recognition. CCBR 2013. Lecture Notes in Computer Science, vol 8232. Springer, Cham. https://doi.org/10.1007/978-3-319-02961-0_37
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DOI: https://doi.org/10.1007/978-3-319-02961-0_37
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-02960-3
Online ISBN: 978-3-319-02961-0
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