Finger vein identity verification method based on ArcFace Loss and improved residual network

Abstract

The invention relates to a finger vein identity verification method based on ArcFace Loss and an improved residual network, and the method comprises the following steps: 1) collecting finger vein images of a plurality of fingers, and carrying out the preprocessing of the images; 2) constructing a convolutional neural network; 3) training a model: training the convolutional neural network by usingArcFace Loss; 4) executing a registration stage: after the registration image is enhanced, inputting the registration image into the trained convolutional neural network to obtain a feature vector, taking an average value as the feature of the finger, and storing the feature as a registration feature library; and 5) executing a verification stage: calculating the cosine similarity between the feature vector and each feature in the registration feature library, and judging whether the feature vector corresponds to a certain finger according to the distance and the threshold. According to the method, the lightweight residual network is improved, so that the expression ability of the lightweight residual network to the finger vein features is effectively improved, the quality of the registration feature library is effectively improved, the whole method is simple, feasible and robust, and the accuracy of finger vein recognition is effectively improved.

Description

technical field [0001] The invention belongs to the biological identification technology in the field of information security, in particular to a finger vein identity verification method based on ArcFace Loss and improved residual network. Background technique [0002] With the development of information technology, people have higher and higher requirements for information security. Technologies such as face recognition and fingerprint authentication have been widely used in people's daily life. However, in the fields of finance and military industry, people often need more secure and reliable biometric technology. Finger vein recognition, as the second generation of biometric technology, has the advantages of in-vivo characteristics, non-replicable, non-contact measurement, and high security level. It has huge potential. research value. [0003] At present, finger vein recognition algorithms can be mainly divided into methods based on finger vein lines, methods based on l...

AI Technical Summary

Problems solved by technology

[0005] The purpose of the present invention is to solve the problem that in the prior art, there are limitations in expressive ability and poor robustness of the algorithm in the finger vein recognition method based on the residual network, and in the recognition method based on the deep learning a

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