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　　 implementation principle and workflow of face recognition system < / a >

　　1. Face image acquisition and preprocessing

Generally, there are two ways to collect face images: batch import of face images and real-time collection of face images. The purpose of preprocessing is to further process the face image based on the detection of the face image by the system, so as to facilitate the feature extraction of the face image

Generally speaking, the recognition system can import various collected face images into the recognition system for processing in batches, or capture the face images to be collected in advance by calling cameras, cameras and other shooting equipment. Here, the laptop with its own camera is selected to complete the early face image acquisition

　　2. Face detection

Complete the first step of image acquisition, and then enter the image detection stage

In a face image, the system will accurately locate the position and size of the face, select useful image information, and automatically eliminate other redundant image information to further ensure the accuracy of image acquisition

　　3. Face feature extraction Here you can open the camera to collect face images. This step mainly aims at some specific feature extraction of face image, collecting and building database

　　4. Face recognition

In the face recognition system, a value of similarity is preset, and then the corresponding face image is compared with all face images in the system database. If the preset value is exceeded, the system will output the exceeded image, which can be 1:1 or 1:n according to the similarity of face image and face identity

For example, if a threshold value of 0.7 is set in the system and the similarity is greater than 0.7 after system comparison, it will be automatically recognized as the same person and the feedback results will be output in the software

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