Research On Anti-counterfeiting Of Vascular Recognition Based On Photoacoustic Technology

In existing recognition technology,biometrics is one of widely used technologies.The existing biometric methods,such as fingerprint recognition,face recognition,iris recognition,and vein recognition.Compared with the previous passwords,ID cards and passwords,they are unique,immutable and not easy to lose,but are vulnerable to malicious spoofing attacks.Therefore,the security of biometrics system requires improvements.With the rapid development of biometrics,methods of spoofing,copying,or forging biometrics pose a significant threat to biometric systems.Therefore,the security of this system requires improvements.This paper adopts a blood vessel recognition system based on photoacoustic imaging to resist deception attacks.In this paper,a set of photoacoustic microscopy systems for laser excitation and ultrasonic imaging with optical resolution are built,including the purchase of lasers,ultrasonic transducers and other instruments,and the design of focusing lens groups.The photoacoustic microscopy system is used as a blood vessel imaging and anti-counterfeiting module: 1.The photoacoustic signal of the detection blood vessel includes the amplitude,speed and maximum arrival time delay(respectively reflecting the light absorption performance of the blood vessel,the material property and the depth information of the blood vessel)Identify fake blood vessels,which can prevent spoofing attacks and help improve the recognition rate.2.Use the peak-to-peak value of the photoacoustic signal to reconstruct the contrast image of the vascular system and the background,and build the photoacoustic blood vessel library.Then this article uses MATLAB to identify the photoacoustic blood vessels: 1.Preprocess the image of the photoacoustic blood vessel library,including normalization,binarization,smoothing,thinning and burr trimming to obtain refined images.2.Use the seven moment invariants to extract the feature values ??of the refined blood vessel image to establish a data set.3.Use SVM to classify and recognize blood vessels.Compared with the method of directly identifying blood vessels,the recognition rate has increased from 95% to 97.5%.The results confirmed the feasibility of photoacoustic blood vessel image recognition,and photoacoustic blood vessel recognition is expected to become one of the best anti-counterfeiting biometrics in the future.