Biometrics and Face Recognition Technology
Steel shearing machines are used by manufacturing companies to cut sheet metal, as well as other materials and workpieces, with a straight blade. The sheet metal is secured below the cutting blade, after which the cutting blade drops down to cut through it. There are many different types of shearing machines, however, one of which is an Alligator Shear. Alligator shears contain a straight-bladed cutting tool as well, but they feature a unique alligator-like design that distinguishes them from other shearing machines.
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Among them, face recognition is one of the most concerned technologies in biometrics for several years. Face recognition refers to the distribution of human facial features and contours. These distribution characteristics vary from person to person and are inherent. Compared with other biometric technologies, face recognition is non-intrusive and can achieve better recognition without disturbing people's normal behavior. Because the devices using face recognition technology can be placed at will, the concealment of the device is very good, and the target recognition object can be quickly and non-contacted at a long distance. Therefore, the face recognition technology is widely used in public security systems abroad, and the application scale is huge.
In many of today's human biometric technologies, face recognition technology is characterized by its strong practicability, high speed, ease of use, and high recognition accuracy, and it has obvious technical advantages when compared with other human biometric identification technologies.
Face recognition workflow includes face image acquisition and detection, face image preprocessing, face image feature extraction, matching and recognition. Face image capture, when the user is within the capture range of the capture device, the capture device will automatically search for and capture the user's face image. Face detection is mainly used for face recognition preprocessing, that is, accurately identifying the position and size of the face in the image, picking out useful information, and using these features to achieve face detection. Face image preprocessing, based on the results of face detection, the image processing and the final service and feature extraction process. Including face image light compensation, grayscale transformation, geometric correction. Face image feature extraction is performed on certain features of the human face to characterize the face. The face image matching and recognition compares the face features to be identified with the face features that have been obtained, and judges the face's identity information according to the degree of similarity.
Face recognition technology application modes, including three modes of portrait retrieval, portrait monitoring, and portrait verification. A portrait search refers to the input of a photo, which is similar to the search in the portrait image database for manual confirmation. It is mainly used in the investigation of the identity of criminal suspects; the verification of the identity of the personnel in exit and entry management; the verification of the identity of consumers and travelers. Portrait monitoring refers to the detection of portraits from the video stream and comparison with a portrait database to automatically identify the person. Apply to criminals to escape; important departments such as entrance control and attendance. Portrait verification means entering two photos to confirm if they are from the same person. Application in the verification of the identity of the holder, e-government, e-commerce, access control of mobile devices.