
Understanding Facial Identification: Face Verification vs. Face Recognition

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Many terms in the biometrics field are used interchangeably, particularly regarding facial verification and face recognition. Although both terms are sometimes used interchangeably, the underlying technologies are different and are intended to assist with various use cases. Thus, it’s crucial to comprehend these differences since they impact how the terms should be used and implemented.
Whilst both use biometric verification and are used to validate individuals, they differ in many ways.
Face Verification: A type of biometric authentication that uses an individual’s biological characteristics to validate that the user is who they claim to be.Â
Face Recognition: A biometric software app that identifies or verifies a person by matching and analysing patterns based on the individual’s facial contours.Â
Face verification is 1:1 compared to facial recognition, which uses a 1:n comparison against a database of recognised faces. The user secures their digital account access by authenticating their face as a credential. The user only needs to snap a selfie to verify, then a biometric template is generated and compared with the stored template. A suitable match completes the safe authentication procedure in the background.
Here are the basic steps of the face verification online process:
Facial recognition validates a user’s face using technology. Advanced face recognition software uses biometrics to map facial traits from a video or photo. The details are then cross-checked with a database of recognised faces to see if there is a match.
Here is how the face recognition process works:
Face recognition software is not error-free. Several variables, including camera quality, database size, and the subject’s gender and race, can substantially impact the precision of face recognition solutions.
Face verification benefits clients and businesses alike. Facial authentication, in contrast to facial recognition technologies which frequently operate without the user’s knowledge, is permission-based, offering a user high levels of security whilst enabling seamless access to their accounts. The appealing aspect of facial verification is that users only need to snap a new selfie to log into their preferred app; they are spared from completing the complete identity verification process.
Businesses can employ facial verification solutions to ensure that only authorised users are setting up and accessing their accounts. Another benefit of facial verification is that companies can use the same biometric information—such as a validated 3D face map—collected during enrolment and reuse it for subsequent authentication occasions. This implies that both ongoing user verification and identity proofing can be handled by the same solution.
Naturally, no technology is entirely risk-free. Due to the volume of data involved in facial recognition, handling and storing challenges may arise. Despite significant advancements, face recognition is still imperfect when faces are seen from different camera angles or when there are barriers like hats. Additionally, there have been privacy-related controversies, especially in the retail and governmental sectors. This is why facial recognition should be combined with multi-factor approaches (such as facial authentication) to improve user access rather than being utilised for identity proofing.
Shufti Pro’s face verification solution uses deep learning algorithms to accurately identify and validate human faces. Shufti Pro is a globally trusted biometric verification solution provider incorporating advanced anti-spoofing measures to combat fraud.
Here’s what makes Shufti Pro’s face verification services a strong barrier against impersonation attacks and stolen identities:
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