Face recognition is a stand-alone application that is rarely used as a modular technology. It is increasingly being applied to people’s lives.So what is face recognition technology?
Face recognition is a biometric recognition technology based on human facial feature information for identification. A series of related techniques for capturing a face or a video stream with a camera or a security camera, automatically detecting and tracking face in the image, and performing face recognition on the detected face, usually called portrait recognition and face recognition.
The Face Recognition System mainly includes four components: Face Image Acquisition and Detection, Face Image Preprocessing, Face Image Feature Extraction, and Matching and Recognition.
Face Image Acquisition and Detection:
Face image acquisition: Different face images can be captured by the camera, such as static images, moving images, different positions, different expressions, etc. can be collected by the cctv camera. When the user is within the shooting range of the collection device, the acquisition device automatically searches for and captures the user’s face image.
Face Detection:Â Face detection is mainly used for pre-processing of face recognition, and the position and size of the face are accurately calibrated in the image.The mode features contained in the face image are very rich, such as histogram features, color features, template features, structural features and so on. Face detection is to screen out useful information and use these features to achieve face detection.
Face Image Preprocessing:
Face image preprocessing is based on the result of face detection, processing the image and ultimately serving the process of feature extraction.The original image acquired by the system is often not directly used due to various conditions and random interference. It must be pre-processed with grayscale correction and noise filtering in the early stage of image processing.
Face Image Feature Extraction:
Face image feature extraction: The features that can be used by the face recognition system are generally divided into visual features, pixel statistical features, face image transform coefficient features, face image algebra features, and the like. Face feature extraction is performed on certain features of the face. Face feature extraction, also known as face representation, is a process of character modeling a face.
Face Image Matching and Recognition:
Face image matching and recognition: The feature data of the extracted face image is searched and matched with the feature template stored in the database. By setting a threshold, when the similarity exceeds the threshold, the result of the matching is output.
Face recognition is to compare the face features to be recognized with the obtained face feature templates, and judge the identity information of the faces according to the degree of similarity.
This process is divided into two categories: one is confirmation, which is a one-to-one image comparison process, and the other is recognition, which is a one-to-many image matching process.
At present, due to the rapid and comprehensive popularity of video surveillance, it takes too much manpower and resources to quickly and accurately find a person from a large number of surveillance video images in a short period of time. Numerous video surveillance applications urgently need a fast identification technology in a long-distance, user-incompatible state, so face recognition technology and face recognition camera emerges as the times require. Using fast face detection, face tracking and face grabbing technology, you can quickly find faces from video surveillance and compare them with the database to quickly identify them and greatly improve the monitoring effect. It has been widely used in government, military, public security systems, public security, and personal information security.
