A novel algorithm of global Gist feature extraction from Dorsal Hand Vein (DHV) image was proposed in order to overcome the defects of losing vein structure in details and the misjudgment of feature points in the existing algorithms. Adopting general biometric identification process, the global Gist features of the DHV gray image is extracted as the texture features after the dorsal hand vein image is reprocessed by image gray normalization pretreatment and filtering enhancement. And then the personal identity was recognized by applying K neighbor classifier. This algorithm was finally verified by using self-established dorsal vein image database. The experimental results show that the proposed algorithm is effective and its correct recognition rate is 96.7%, and so the application prospect is broad employed.
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