Fake fingerprint detecting method based on SVM and sparse representation

Abstract

The invention discloses a fake fingerprint detecting method based on a SVM and sparse representation. The method comprises the steps of collecting hundreds of true and fake fingerprint images, extracting characteristic data of statistical characteristics, frequency domain characteristics and the like, uniformizing the characteristic data, carrying out supporting vector machine (SVM) training to obtain classification models of the SVM, extracting images of fingerprints needing to be detected, extracting and uniformizing the same characteristic data, classifying the classification models of the SVM to obtain true or fake SVM classification results, randomly extracting subimages of the fingerprint images, training a sparse representation dictionary, randomly extracting subimages of the fingerprint images needing to be detected, carrying out sparse representation to judge the subimages as true subimages or fake subimages, and finally using the classification and judgment results to carry out compound decision. The method needn't improve fingerprint collecting hardware, is quick in computation speed and high in accuracy and has important application value in improving safety of a fingerprint recognizing system.

Description

technical field [0001] The invention relates to the field of biological feature recognition, in particular to image processing and pattern recognition. Background technique [0002] At present, fingerprint identification is widely used in various security systems, and the identification performance including accuracy rate and speed is relatively good. [0003] However, criminals can use various materials to make fake fingerprints and pass through the fingerprint recognition system. True fingerprints, also known as living fingerprints, refer to fingers with human biological functions, that is, fingers of a living human body. The corresponding false fingerprints are also called dead body fingerprints, including fingerprints made of materials, such as silica gel, clay, paper with printed fingerprint images, etc., and even fingers that leave the human body are called dead body fingerprints. [0004] The collection of fake fingerprints is different from the collection of real f...

AI Technical Summary

Problems solved by technology

[0005] It is worth pointing out that many literatures point out the difference between true and false fingerprints, such as white spots (pores) in the middle of the black stripes of real fingerprints, damaged black stripes of fake fingerprints, black specks in white stripes of fake fingerprints, and black spots in the white stripes of fake fingerprints. The difference between black and white stripes is not clear, and the width of stripes of real and fake fingerprints is different, etc., all appear in the real and fake fingerprint images actually extracted, and it is impossible to judge the real and fake by human eyes. See the real fingerprint image example figure 2 , for an example of a fake fingerprint image, see image 3

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