Abstract
To solve the problem of low recognition performance caused by contact-less imaging and poor palm vein image quality, a novel recognition method is proposed. Firstly, the ROI based on the thenar (a part of palm) is located; secondly, the palm vein features based on wavelet decomposition and partial least square are extracted; finally, the images are matched by Euclidean distance. In self-build palm vein database, the experimental result shows that the best recognition rate of this method reaches 99.86%. Comparing with the other typical palm vein recognition methods, the performance of proposed approach is the best. In conclusion, the scheme can improve the identification performance of contact-less palm vein recognition significantly.
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Wu, W., Yuan, Wq., Guo, Jy., Lin, S., Jing, Lt. (2012). Contact-Less Palm Vein Recognition Based on Wavelet Decomposition and Partial Least Square. In: Zheng, WS., Sun, Z., Wang, Y., Chen, X., Yuen, P.C., Lai, J. (eds) Biometric Recognition. CCBR 2012. Lecture Notes in Computer Science, vol 7701. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-35136-5_22
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DOI: https://doi.org/10.1007/978-3-642-35136-5_22
Publisher Name: Springer, Berlin, Heidelberg
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