Multi-feature fusion-based massive fingerprint coding and comparing method

Abstract

The invention relates to a multi-feature fusion-based massive fingerprint coding and comparing method. The method comprises the steps of inputting massive registration fingerprints and a to-be-identified fingerprint and respectively marking all the registration fingerprints with the only ID identification codes; respectively constructing characteristic matrixes and minutiae matrixes for the to-be-identified fingerprint and all the registration fingerprints; constructing a rapid fingerprint screening tree; registering the registration fingerprints with similar characteristic evaluation indexes on leaf nodes of the screening tree to form a like registration fingerprint list; searching the registration fingerprint list with the similar characteristic evaluation index to that of the to-be-compared fingerprint in the rapid screening tree by utilizing the characteristic matrix of the to-be-compared fingerprint, counting the frequency of each fingerprint ID identification code in the list and taking out a plurality of fingerprints with the highest frequency to form a registration fingerprint suspect queue; and comparing the minutiae matrix of the to-be-compared fingerprint with the minutiae matrixes of the registration fingerprints in the suspect queue one by one and finally obtaining the registration fingerprint with the highest comparison similarity to serve as the comparison result of the method.

Description

technical field [0001] The invention provides a multi-feature fusion mass fingerprint encoding and comparison method, which belongs to the field of biological feature identification, and in particular relates to a fingerprint identification method. Background technique [0002] Compared with other biometric identification technologies, fingerprint automatic identification technology has excellent accuracy and high economic practicability. Fingerprint identification technology is divided into two processes: (1) fingerprint registration process. By reading the fingerprint image, the fingerprint area in the fingerprint image is found, and the features in the fingerprint area that can distinguish the fingerprints from each other are extracted. Save these feature data in the database and use it as the representative of this fingerprint to complete the fingerprint registration process; (2) feature comparison process. After extracting the features of the newly collected fingerpri...

AI Technical Summary

Problems solved by technology

For massive fingerprints (such as hundreds of millions or even billions of fingerprints), on the one hand, when extracting fingerprint features, it is not possible to construct fingerprint features with the ability to accurately distinguish massive fingerprints only by using traditional minutiae features or line features; On the other hand, the idea of ​​comparing the fingerprints to be compared with all the registered fingerprints one by one is not advisable due to the huge workload of the comparison, and it will consume the comparison time in units of months

Images