Fingerprint and finger vein bimodal recognition decision level fusion method

A decision-level fusion and finger vein technology, applied in the field of pattern recognition, can solve problems that remain in theory, and achieve the effects of improving influence, reliable recognition results, and strong practicability
CN101901336AInactive Publication Date: 2010-12-01HARBIN ENG UNIV
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Patent Information

Authority / Receiving Office
CN · China
Current Assignee / Owner
HARBIN ENG UNIV
Publication Date
2010-12-01
Estimated Expiration
Not applicable · inactive patent

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Abstract

The invention provides a fingerprint and finger vein bimodal recognition decision level fusion method. Two modules, namely a fingerprint module and a vein module are included. The fingerprint module and the vein module read fingerprint images and vein images; the read fingerprint images and vein images are subjected to image quality evaluation according to respective image characteristics to acquire quality scores; the fingerprint images and vein images are preprocessed and recognized, wherein the fingerprint recognition adopts a minutiae-based matching method and the vein recognition adopts an improved Hausdorff distance mode, and respective recognition results are obtained; and finally, a weight is designed according to image quality scores of the two modes, and the recognition results are subjected to decision level fusion according to the weight and a final recognition result is obtained. Based on the fact that the performance of the system after fusion is superior to that of a single fingerprint recognition or finger vein recognition system, the method has strong practicability.
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Description

technical field

[0001] The invention belongs to the technical field of pattern recognition, and in particular relates to fingerprint recognition, finger vein recognition and a decision-level fusion method thereof. Background technique

[0002] Multimodal biometric identification technology is a method of integrating evidence scores provided by multiple or multiple biometric sources to make more accurate and rapid decisions. The application of multi-modal biometric identification technology makes up for the shortcomings of single biometric authentication, which is unstable and has a high error rate. Research in this area began in 1995. Brunelli and Falavigna proposed a dual-mode biometric recognition system based on voice and face features, which achieved good results; in 1996, Maes first realized a combination of biometrics ( Fingerprint) and non-biological characteristics (password) system; in 1997, Bigun proposed a Bayesian method that integrates different biological char...

Claims

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