Abstract
In order to improve the recognition accuracy with high speed, a palm vein identification method based on multi-direction gray surface matching is proposed. The algorithm extracts region of interesting (ROI) of palm vein image firstly. Then, it computes the multi-direction gray scale’s difference in the matching of surface of two ROI. The variances of the multi-direction grayscale difference surface are calculated and the minimum of variance is considered as the distance between two feature surfaces. At last, the algorithm decides whether these two images come from the same hand or not according to the distance. In the self-build palm vein database, the recognition rate of this method reaches 98.48% and the speed is 21.8ms. Comparing with other typical palm vein recognition methods, the proposed approach improves CCR and decreases FAR.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
Similar content being viewed by others
References
Pan, M., Kang, W.: Palm vein recognition based on three local invariant feature extraction algorithms. In: Sun, Z., Lai, J., Chen, X., Tan, T. (eds.) CCBR 2011. LNCS, vol. 7098, pp. 116–124. Springer, Heidelberg (2011)
Lee, J.C.: A novel biometric system based on palm vein image. Pattern Recognition Letters 33(12), 1520–1528 (2012)
Wang, J., Yau, W., Suwandy, A., et al.: Fusion of palmprint and palm vein images for person recognition based on “Laplacianpalm” feature. Pattern Recognition 41(5), 1514–1527 (2008)
Wu, W., Yuan, W., Lin, S., Song, H., Shang, H.: Fast Palm Vein Identification Algorithm Based on Grayscale Surface Matching. Acta Optica Sinica 33(10), 1015004 (2013)
Watanabe, M., Endoh, T., Shiohara, M., et al.: Palm vein authentication technology and its applications. In: Proceedings of the Biometric Consortium Conference, pp. 19–21. IEEE Press, Arlington (2005)
Wang, L., Leedham, G.: Near-and far-infrared imaging for vein pattern biometrics. In: Proceedings of the Video and Signal Based Surveillance, pp. 52–57. IEEE Press, Sydney (2006)
Watanabe, M.: Palm Vein Authentication in Advances in Biometrics, pp. 75–88. Springer, Heidelberg (2008)
Lee, E.C., Park, K.R.: Image restoration of skin scattering and optical blurring for finger vein recognition. Opt. Lasers Eng. 49, 816–828 (2011)
Wu, W., Yuan, W.Q., Lin, S., et al.: Study of ROI selection and location for palm vein recognition. Journal of Optoelectronics∙Laser 24(1), 152–160 (2013)
Wu, X., Zhang, D., Wang, K.: Palmprint Recognition, pp. 9–10. Science Press, Beijing (2006)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2014 Springer International Publishing Switzerland
About this paper
Cite this paper
Wu, W., Jin, W., Guo, JY. (2014). Palm Vein Identification Based on Multi-direction Gray Surface Matching. In: Sun, Z., Shan, S., Sang, H., Zhou, J., Wang, Y., Yuan, W. (eds) Biometric Recognition. CCBR 2014. Lecture Notes in Computer Science, vol 8833. Springer, Cham. https://doi.org/10.1007/978-3-319-12484-1_32
Download citation
DOI: https://doi.org/10.1007/978-3-319-12484-1_32
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-12483-4
Online ISBN: 978-3-319-12484-1
eBook Packages: Computer ScienceComputer Science (R0)