A finger vein recognition method and device based on deep correlation feature learning

A technology of feature learning and identification method, applied in the field of biometric identification, can solve the problem of inability to accurately identify thin veins, achieve good economic and social benefits, improve identification accuracy, and strong identification performance.
CN110263726BActive Publication Date: 2021-02-02INSPUR GROUP CO LTD
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Patent Information

Authority / Receiving Office
CN · China
Patent Type
Patents(China)
Current Assignee / Owner
INSPUR GROUP CO LTD
Publication Date
2021-02-02

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Abstract

The invention discloses a finger vein recognition method and device based on deep correlation feature learning, which belongs to the field of biometrics. The technical problem to be solved by the invention is how to effectively and precisely identify finer veins, and establish the relationship between detail points. Relevance information to ensure strong recognition performance. The technical solution adopted is: ①The steps of the method are as follows: S1. Extract detail points; S2. Build graph nodes; S3. Learn correlation map: correlation based on RankSVM Graph mapping learning method, obtaining the adjacency matrix of the correlation graph, reflecting the correlation information between graph nodes; S4, deep correlation feature learning; S5, matching: combining the obtained effective deep correlation features with the templates stored in the database Perform similarity comparison to complete the matching task. ② The device includes a minutiae point extraction module, a graph node construction module, a correlation map learning module, a deep correlation feature learning module, and a matching module.
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Description

technical field

[0001] The invention relates to the field of biological identification, in particular to a method and device for identifying finger veins based on deep correlation feature learning. Background technique

[0002] With the progress of society, technology in various fields has made great progress. Biometric identification technology uses human biological characteristics or behavioral characteristics for human identity authentication. Among them, human biological characteristics mainly include two categories: external biological characteristics and internal biological characteristics. External biometrics such as fingerprints, iris vision, and face shape. Internal biometrics such as finger veins etc. Finger vein recognition is an emerging biometric technology with great potential. It has the advantages of internal features and living body recognition, and has attracted more and more researchers and developers' attention. Feature extraction is a key part of vein...

Claims

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