High level authentication system using palm vein based on deep neural network

Electronics and communication engineering

Palm print provides a reliable source of information for automatic personal identification and has wide and important applications. This paper mainly focuses on feature analysis of palm print biometrics. And the details of palm print image preprocessing can be found in the existing publications. For palm print images, the gaps between neighboring fingers can be used as the landmark points for correction of the rotation and scale changes of palm print images and then the central region can be cropped as the input of feature analysis. The basic idea of the proposed feature selection method is to find a sparse representation of ordinal features on the condition of large margin principle. On one hand, the intra and inter-class biometric matching results are expected to be well separated with a large margin. On the other hand, the number of selected ordinal features should be much smaller than the large number of candidates.

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