Secondary classification fusion identification method for fingerprint and finger vein bimodal identification

Abstract

The invention provides a secondary classification fusion identification method for fingerprint and finger vein bimodal identification. A fingerprint module and a vein module are used as primary classifiers, and a secondary decision module is used as a secondary classifier. The method comprises the following steps of: reading a fingerprint image and a vein image through the fingerprint module and the vein module; pre-processing the read images respectively and extracting characteristic point sets of the both; performing identification on the images respectively to obtain respective identification results, wherein the fingerprint identification adopts a detail point match-based method, and the vein identification uses an improved Hausdorff distance mode to perform identification; forming a new characteristic vector by using the extracted fingerprint and vein characteristic point sets in a characteristic series mode through the secondary decision module so as to form the secondary classifier and obtain an identification result; and finally, performing decision-level fusion on the three identification results. The method has the advantages of making full use of identification information of fingerprints and finger veins, and effectively improving the accuracy of an identification system, along with high identification rate.

Description

technical field [0001] The invention belongs to the technical field of pattern recognition, in particular to a method for recognizing through fingerprints and finger veins. Background technique [0002] The information collected by the single-mode biometric identification system is susceptible to changes due to time, environment or other factors, and the defects of feature extraction and matching lead to an excessively high error rate, which makes the application environment have too many restrictions and each biometric It is also impossible to be universal in a true sense, and these problems are difficult to solve by simply improving the matching method. The multi-modal biometric identification can provide more sufficient identification information through the combination of multiple biometric features, which makes up for the shortcomings of single biometric authentication such as instability and high error rate, improves the recognition rate of the system, and enhances the...

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Problems solved by technology

However, vein recognition has the disadvantage of few features that can be extracted

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