Convolutional variational auto-encoder neural network-based finger vein identification method and system

Abstract

The invention discloses a convolutional variational auto-encoder neural network-based finger vein identification method and system. The system comprises an image collection module, an image preprocessing module, an image feature extraction module, an image training module and an image identification module. The identification method comprises the steps of obtaining a finger vein image of a to-be-identified user; performing image preprocessing on finger vein image information, and extracting a finger vein region-of-interest (ROI) image; extracting finger vein feature codes in a finger vein ROIthrough the convolutional variational auto-encoder neural network; and inputting the feature codes to a full connection network for performing identification processing, thereby identifying identity information of the to-be-identified user. The finger vein features can be effectively extracted; the noise redundancy is improved; and the identification precision of the finger vein identification system is remarkably improved.

Description

technical field [0001] The present invention relates to biometric identification method, in particular to a kind of finger vein identification method and system based on convolutional variational self-encoder neural network. Background technique [0002] Biometric technology is a technology for human identity authentication through human biological characteristics or behavioral characteristics. Among them, behavioral characteristics include gait, voice, signature, etc. Human biological characteristics mainly include two categories, external biological characteristics: such as face shape, palm shape, fingerprint, iris, etc.; internal biological characteristics: such as palm veins, finger veins and dorsal hand veins Wait. Currently common identification methods such as fingerprints, voice, signatures, faces, etc. are easy to forge and fragile, and the detection methods of iris, DNA, etc. are complex and unfriendly. [0003] Finger vein recognition is an identification techno...

AI Technical Summary

Problems solved by technology

However, in the process of finger vein recognition, the traditional finger vein image recognition method is affected by many factors, and has the following defects in practical application: 1) it is easily affected by the environment in the finger vein image acquisition, in many cases such as ambient light, Ambient temperature and light scattering will affect the recognition rate; 2) vein images are susceptible to noise interference and affect the distribution of vein features in the image; 3) usually, it is difficult to establish an effective mathematical model to extract the distribution of each distribution. feature

Therefore, the current methods based on manual features are difficult to effectively extract finger vein pattern information, resulting in limited recognition performance of the authentication system.

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