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

Abstract

The invention discloses a living fingerprint detection method based on a thin-plate spline deformation model. The fingerprint sequence of the finger to be tested is collected and preprocessed; the fingerprint images before and after deformation are registered, and the corresponding detail feature point pairs are selected as the estimated thin-plate spline The reference point pair of the model; the improved thin-plate spline model is used to describe the deformation of the fingerprint; the deformation energy of the fingerprint to be tested in each direction is calculated based on the model parameters, and the overall bending energy vector is formed; respectively trained on the deformation database of true and false fingerprints to obtain The spatial distribution of the bending energy vector; respectively calculate the similarity between the bending energy vector to be tested and the true and false bending energy fuzzy feature sets; select an appropriate threshold to obtain the detection result. The invention can detect false fingerprints from living fingerprints, realize real-time and effective detection of living fingerprints, improve the security of an automatic fingerprint recognition system, broaden its application range, and have important application value in the field of biometric 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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