Facial Recognition System; a Technology Capable Of Matching a Human Face from a Digital Image or Video Frame
Facial recognition system is a software that maps an individual's facial features mathematically and stores the data as a faceprint. The software compare a digital image to the stored faceprint to verify an individual's identity. Facial recognition is a way of identifying and/or confirming an individual's identity using their face. It is a category of biometric security. Facial recognition system uses biometrics to map facial features from a photo or video. The system compares the information with a database of known faces to find a match, and helps verify a person's identity. The system is mainly used in security purposes, and also have application in different areas, such as payment, access control, and others.
According to Coherent Market Insights the Facial Recognition System Market Size, Share, Outlook, and Opportunity Analysis, 2022-2028.
Face recognition systems use computer algorithms to pick out specific, distinctive details about a person's face. These details, such as distance between the eyes or shape of the chin, are then converted into a mathematical representation and compared to data on other faces collected in a face recognition database, and verify a person's identity. It is an effective way of categorizing and identifying people, and can be combined with other identifying factors, such as passwords and fingerprints, to increase security and convenience. It is both touchless and safe method of identification, and some organizations have started using this technology. In the travel industry, it is now being used to speed up check-in and ticketing processes.
The technology uses nodal points on a human face to measure the various variables of the face. These points are captured to form a digital image, and then the system compares that image with images stored in the system to verify a person's identity. In some cases, facial recognition systems are as accurate as human beings, but it is still not foolproof. This technology is still not perfect, but it is becoming increasingly reliable. It normalizes and compresses a gallery of face images, and then compares probe image to the target face. A template-matching method is one of the earliest systems, and is used to match faces. The algorithm then divides unknown faces into smaller groups, using a list of salient facial features.
One of the most widely used facial recognition systems uses a technique known as a template matching. This method uses a set of salient facial features to match faces in a database. These features can be found on millions of images. After training, a software compares these features to the data from different faces in the database. The system then uses these measurements to determine which face matches the probe image. Eventually, it can identify faces from a variety of photos in a short amount of time. Facial recognition is used when issuing identity documents and, most often, combined with other biometric technologies such as fingerprints (preventing identity (ID) fraud and identity theft).
Face match is used at border checks to compare the portrait on the digitized biometric passport with the holder's face. U.S. Customs and Border Protection used facial recognition technology on more than 23 million travelers in 2020, according to a report published by the agency. That's up from the 19 million travelers CBP scanned with the tech in 2019. The biometric facial scans had a match rate of more than 97% last year, according to the agency.