Face recognition system based on silent living body detection

Abstract

The invention discloses a face recognition system based on silent living body detection. The face recognition system comprises a data acquisition module, a data preprocessing module, a face detection module, a living body detection module and a face recognition module; the living body detection module carries out living body detection by using models of three levels, respectively carries out living body or attack classification on the whole photo, carries out living body or attack classification on the face area photo and carries out attack feature detection on the whole photo; the detected objects comprise moire patterns, abnormal light and shadow, mobile phone frames, photograph holding, display light reflection, plastic material light reflection and the like; according to the face recognition system, the attack or the living body can be distinguished only by performing transient shooting on the front face of the user towards the screen, the model in the living body detection module has good generalization ability and high recognition precision, the attack success probability is effectively reduced, the user safety is ensured, and the invention is suitable for various face recognition scenes such as identity authentication and unlocking login.

Description

technical field [0001] The invention relates to a face recognition system, in particular to a face recognition system based on silent living body detection. Background technique [0002] In recent years, face recognition technology has been widely used. In order to prevent malicious people from forging and stealing other people's photos or images for identity authentication and to ensure user safety in face recognition systems, liveness detection is required. Currently, liveness detection is mainly divided into two categories: The class is based on the liveness detection of the image classification model, which needs to collect nearly a million samples to ensure the accuracy of the liveness detection in a limited scene. The generalization ability for scenes other than the data set is poor, and the recognition speed and accuracy are low; another This type is cooperative liveness detection, which requires the user to cooperate to complete actions such as turning the head and b...

AI Technical Summary

Problems solved by technology

[0002] In recent years, face recognition technology has been widely used. In order to prevent malicious people from forging and stealing other people's photos or images for identity authentication and to ensure user safety in face recognition systems, liveness detection is required. Currently, liveness detection is mainly divided into two categories: The class is based on the liveness detection of the image classification model, which needs to collect nearly a million samples to ensure the accuracy of the liveness detection in a limited scene. The generalization ability for scenes other than the data set is poor, and the recognition speed and accuracy are low; another This type is cooperative liveness detection, which requires the user to cooperate to complete actions such as turning the head and blinking eyes, and the user experience is poor

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