Convolutional neural network-based embedded finger vein identification method enabling counterfeit detection capability

Abstract

The present invention discloses a convolutional neural network-based embedded finger vein identification method enabling a counterfeit detection capability. The method includes the following steps that: S1, a plurality of finger vein images of a plurality of levels of light intensities are acquired, a finger vein image with the highest resolution is selected, the ROI (region of interest) of the captured image is preprocessed; S2, a local binary pattern (LBP) is utilized to perform texture feature coding on the high frequency information of the finger vein image; S3, the high frequency part features of the finger vein image are extracted through using a high-pass filter, finger image features are extracted through a vein identification shallow convolutional neural network; and S4, an SVM (support vector machine) classifier is utilized to perform counterfeit detection so as to distinguish the authenticity of the vein image. With the method adopted, the problem that a printed counterfeited vein image can fool an existing identification system can be solved, and the security of an actual vein identification system can be improved; the problem of the decrease of the identification accuracy of the actual system which is caused by factors such as low vein image quality and finger axial deflection can be solved.

Description

Technical field [0001] The invention relates to the technical fields of biological feature recognition, image processing and pattern recognition, and deep learning, in particular to an embedded finger vein recognition method based on a convolutional neural network and having a counterfeit detection capability. Background technique [0002] Biometric recognition technology refers to the use of unique physiological or behavioral characteristics of a person, such as face, fingerprint, iris, palmprint, voiceprint and signature, etc., through some pattern recognition algorithms for identity recognition. Compared with traditional identification methods, biometric identification technology is more reliable, safe and convenient. Finger vein recognition technology, as an emerging biometric identification technology, has gained a place in the field of biometric identification with its unique live detection capabilities. Compared with other biometric identification, finger vein recognition ...

AI Technical Summary

Problems solved by technology

Although its current development trend is good, due to the problem of its own imaging mechanism, the image quality collected by the existing finger vein recognition system is not high. The main reasons include: the design problem of the collection device, and the different thickness of different fingers is not fully considered. The situation; the image deviation caused by the axial deflection of the finger is not considered, so the current system basically does not have an effective algorithm for the axial deflection of the finger during the authentication process. Therefore, it is necessary to strictly restrict the position of the finger to reduce the user experience.

In addition to the problem of low image quality, some recent studies have found that some vein forgery techniques can attack and deceive the existing recognition system, which seriously affects the security of the finger vein recognition system.

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