Posture correcting based fingerprint retrieval method and system

Abstract

The invention discloses a posture correcting based fingerprint retrieval method and system. The retrieval method includes steps of acquiring posture information of a plurality of fingerprint images in a fingerprint map database; subjecting each fingerprint image to posture correcting; obtaining errors of the posture correcting algorithm by training the fingerprint images; partitioning each fingerprint image into many areas according to the errors and setting up a reverse index table, a fingerprint map database and a reverse index table for training the fingerprints in the same area in the many fingerprint images; studying the number of detail points corresponding to keywords and mapping among weights and establishing weighting functions; subjecting inquired fingerprints to posture correcting and retrieving via the weighting functions and the reverse index tables of the fingerprint map database. According to the fingerprint retrieval method in the embodiment, by subjecting the many fingerprint images in the fingerprint map database to posture correcting and partitioning each fingerprint image and by retrieving the fingerprint map database after subjecting the inquired fingerprints to posture correcting, retrieval accuracy and efficiency are improved.

Description

technical field [0001] The invention relates to the technical field of fingerprint retrieval, in particular to a gesture correction-based fingerprint retrieval method and system. Background technique [0002] In related technologies, mainstream fingerprint retrieval methods are based on minutiae descriptors and posting list technology. Among them, the minutiae descriptor can be a feature in the neighborhood of a single minutiae, or an attribute of a minutiae pair or a minutiae triplet. The retrieval method in the related art includes an offline indexing stage and an online query stage. Specifically, in the offline stage, all the minutiae descriptors of library fingerprints are mapped into keywords through direct quantization methods or hash functions, etc., and the minutiae numbers are stored in the corresponding keywords to form an inverted index table; In the same way, the minutiae descriptors of the query fingerprint are mapped to keywords. It is generally considered th...

AI Technical Summary

Problems solved by technology

[0003] However, the fingerprint retrieval method in the related art ignores the pose constraints, resulting in many mismatched descriptors for unmatched fingerprints, which limits the performance of the retrieval method and the retrieval accuracy is not high.

In addition, there are retrieval methods in the related art that cluster the transformation parameters of the matching minutiae points, and then delete the matching points inconsistent with the optimal transformation parameters. Although the pose constraints are used, the accuracy is higher than without the pose constraints, but the speed is very slow. , resulting in low retrieval efficiency

Images