The main function module of face verification system
The face verification system is an identity encryption technology based on the terminal camera, whose core is the face recognition technology. It confirms the identity of the user through a video scan. When the user enters the login interface, the terminal will automatically transfer the user image to the face recognition system through the camera. After the system analyzes and identifies the face features, it determines whether the user is legal.
The use of face verification system can eliminate tedious password input, and the interaction is faster and more convenient. In addition, as a typical biometric identification technology, face registration technology also has some advantages that other encryption methods cannot match. For example, it has the capability of tracking afterwards. The face authentication system can save the face images of the parties at the same time as the login event occurs. Even if the management personnel do not understand the technology, the events can be monitored and reviewed in an intuitive manner, which ensures that the system has a good post-event tracking capability.
The main function module of face verification system:
Face capture and tracking:
Face capture refers to the detection of a portrait in a frame of an image or video stream and the separation of the portrait from the background and automatic preservation. Portrait tracking refers to the use of portrait capture technology that automatically tracks a specified portrait while it is moving within the camera's range of shooting.
Face recognition comparison:
Face recognition sub-verification and search-type two matching modes. Verification is to confirm whether the captured person or the specified person is compared with a registered person in the database to determine whether he is the same person. The search-style comparison refers to searching from all portraits registered in the database to find out if a specified portrait exists.
Face modeling and retrieval:
The registered portrait data can be modeled to extract the features of the human face, and the generated face template (face signature file) can be saved in the database. When performing a face search (search formula), the specified portrait is modeled and compared with the template of all the people in the database. Finally, the most similar person is listed according to the similarity value compared. List.
Human identification function:
The system can identify whether the person in front of the camera is a real person or a photo. In order to prevent users from using photographs to fake. This technology requires the user to make facial expressions.
Image quality detection:
The quality of the image directly affects the effect of the recognition. The image quality detection function can evaluate the image quality of the photos to be compared, and give corresponding recommended values to assist the recognition.
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