Anti-spoofing System On Mobile Phone Based On Face Recognition Technology

Smart phone Anti-spoofing system is a technology for mobile payment service,including internet of things,internet plus finance,the concept of smart city,combined with the current popular 4G communication,face recognition technology,for existing mobile payment applications.Toavoidthe use of inconvenience,experience is not good enough,real-name authentication rare problem.The construction of a real-time good,fast response,strong security level and good experience Anti-spoofing system onsmart phone.The application of advanced biometric detection technology to the registration of mobile payment applications,real-name system certification,payment verification and other links,to build a relatively mature,has been used mobile payment verification program.The following results are as following: Adaboost face detection algorithm based on Haarlike feature and face recognition based on Gabor wavelet are analyzed in the ideal illumination that the detection and recognition performance of the collected image is high,but the image acquired in the case of the light masking part of the face is detected and the performance of the recognition is largely reduced.In order to solve the effect of light masking on the detection and recognition performance,this paper chooses the best performance algorithm combined with Adaboost face detection classifier by comparing the effect of Retinex correlation algorithm on image illumination preprocessing,which improves the face detection rate in the effect of light blocker effectively.It provides a complete idea for the system OCR module,face recognition comparison module,Anti-spoofing module and database construction,as well as the process of combing the business process,the finishing of business rules and the determination of business logic in the process of realization.The system compared to the traditional mobile payment system with advanced technology.At the end of this paper,the operation of the mobile phone body detection system was tested and analyzed,and the system completion degree and subsequent optimization direction were obtained.