Abstract
Based on the Retinex method and the SIFT feature analysis, this paper presents a novel algorithm for hand vein recognition. First of all, the principle of the near-infrared hand vein image acquisition is introduced. Secondly, the Retinex method is used to normalize hand vein images, and the adaptive smoothing method is selected to estimate the illumination. Then gray cosine transform is used to enhance the discrimination of the skin and the vein in hand vein images. Thirdly, the SIFT feature analysis algorithm is used to extract the feature of hand vein. Finally, the match method of two hand vein images based on SIFT is given. A hand vein recognition system in Microsoft VC6.0 is also developed and the experimental results demonstrate the high efficiency of the proposed algorithm in runtime and correct recognition rate.
This work is supported by the Key Project of the Natural Science Research in Anhui Provincial Higher Education Instructions under Grant No. KJ2010A011.
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Wang, Hb., Tao, L., Hu, Xy. (2011). Novel Algorithm for Hand Vein Recognition Based on Retinex Method and SIFT Feature Analysis. In: Wan, X. (eds) Electrical Power Systems and Computers. Lecture Notes in Electrical Engineering, vol 99. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-21747-0_70
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DOI: https://doi.org/10.1007/978-3-642-21747-0_70
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