Abstract
Based on the DEFD-SIFT feature analysis, this paper presents a novel algorithm for hand vein feature extraction and recognition. First of all, the principle of the near-infrared hand vein image acquisition is introduced. Secondly, the SIFT feature analysis algorithm is used to extract the feature of hand vein. We designed a novel neighborhood descriptor, which is called “Double Ellipses Feature Descriptor”. The local texture feature is extracted effectively, while reducing the interference of skin region. Finally, the SIFT feature matching algorithm based on similarity measure is given and the experimental results demonstrate the high efficiency of the proposed algorithm in runtime and correct recognition rate.
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