Method for detecting living body fingerprint based on thin plate spline deformation model

Abstract

The invention discloses a living fingerprint verifying method based on a thin-plate spline deformable model, which collects and preprocesses the fingerprint sequence of a finger for verifying, registers the fingerprints before and after deformation, selects corresponding minutiae point pair to serve as the criterion point pair for estimating the thin-plate spline model, employs improved thin-plate spline model to describe deformation of fingerprints, computes the deformable energy of the fingerprint for verifying in each direction on the basis of model parameter to an overall bending energy vector, trains respectively on a true and a false fingerprint deformation base, obtains space distribution of the bending energy vector, respectively computes similarity from the bending energy vector for measuring to an eigen fuzzy set of true and false bending energies, and selects proper threshold value to obtain the verifying result. The invention can identify false fingerprint from the living fingerprint, effectively realizes living fingerprint verification in real-time, increases safety of automatic fingerprint verifying systems, enlarges the application range of automatic fingerprint verifying systems and has important application value in the field of biological character identification.

Description

technical field [0001] The invention belongs to the field of biological feature identification, and relates to frontier knowledge such as image processing, pattern recognition, and computer technology, and in particular relates to fuzzy classification of fingerprint deformation and deformation energy vectors described by a thin plate spline (TPS) model. Background technique [0002] Due to the advantages of uniqueness and stability, convenient collection and low cost, fingerprints are very suitable to replace traditional passwords as a reliable means of identity authentication. Input the fingerprint image to be matched into the computer, and through the reliable and effective fingerprint recognition algorithm, the identity recognition of anyone can be completed in a short time. Fingerprint identification technology mainly includes fingerprint image acquisition, fingerprint image enhancement, fingerprint image feature extraction, data storage, comparison and matching of finge...

AI Technical Summary

Problems solved by technology

The method of using hardware to detect static physical characteristics such as temperature, smell, and resistance of human fingers to distinguish fake fingerprints cannot avoid making more simulated fake fingerprints for identification attacks

Moreover, the support of special hardware is required, which increases the cost of the fingerprint recognition system and is not easy to promote

The detection method based on the characteristics of the fingerprint itself may not be suitable for fingerprints with special skin conditions or not real-time

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