Time: 2021-08-27 View: 784
Face recognition is an independent application rarely used as modular technology, which has been more and more used in people's life.
Face recognition is a biometric recognition technology based on face feature information.Detects and automatically tracks the face in the image, and carries out detected face recognition, which is usually called portrait recognition and face recognition.
The face recognition system mainly includes four parts: face image acquisition and detection, face image preprocessing, face image feature extraction, matching and recognition.
Face image acquisition and detection: face image acquisition: the camera can collect different face images, such as static images, dynamic images, different positions, different expressions, etc. CCTV camera can collect the user's information. When the user is within the acquisition range of the acquisition device, the acquisition device will automatically search and collect the user's face image.
Face detection: face detection is mainly used for the preprocessing of face recognition, preprocessing the position and size of the face in the image. The face image contains rich tr-s pattern features, such as histogram features. Face detection includes filtering useful information and using these features to realize face detection.
Face image processing: face image processing is to process the image based on the results of face detection, and finally serve the feature extraction process. The original image obtained by the system can not be used directly due to various conditions and interference. In order to process the image, gray scale correction and noise filtering preprocessing must be carried out.
Face image feature extraction: face image feature extraction: the features that can be used by face recognition system are generally divided into visual features and pixel statistical features. Transform coefficient feature of face image, alg feature brick of face image, etc. face feature extraction is to extract some face features. Face feature extraction, also known as face representation. It is a modeling process of facial features.
Face image matching and recognition: face image matching and recognition: extract feature data from the extracted face image and compare it with the feature pattern stored in the database. By setting the threshold, when the similarity exceeds the threshold, Generate corresponding r results. Face recognition is to compare the recognized face features with the obtained face feature model, and judge the face features according to the similarity. The process is divided into two categories: confirmation, which is an image comparison process; recognition, which is an image matching process.
At present, due to the rapid and comprehensive popularization of video surveillance, Finding a person quickly and accurately from a large number of video surveillance images in a short time requires a lot of human and material resources. Many video surveillance applications urgently need remote rapid recognition technology and video surveillance technology. Due to the incompatibility of users' states, face recognition technology and face recognition camera appear. Through fast face detection, face tracking and face capture technology, faces can be quickly found from video surveillance. Compared with ES database, fast face recognition can greatly improve the monitoring effect, and has been widely used in the fields of government, e-government, public security system, public security and personal information security.