Have you ever considered the process of identification? Internal facial recognition and identification are part of this procedure. Our minds analyze particular aspects of the face and compare them to the faces we can remember. The process is enjoyable and moves rapidly. It also forms the foundation for some contemporary contactless technologies that boost corporate security, like facial recognition terminals.
Examine if the selfie your users take is indeed in progress, if it was correctly clicked to save it in your records, if there are any other faces visible, and what area of the picture the face actually takes up.
Face liveness Check API helps in the identification of frauds by ensuring that the image you have been given isn’t a passport image, or an image, picture of a picture of another person on a mobile device or laptop screen. Pair it with the Face Liveness detection to be completely assured that the selfie is real and belongs to the person you expect.
We have developed the best liveness detection anti-spoofing solution. It demonstrates that the provided recordings are from real, live persons who faced the camera. The level of confidence for real-time online transactions is greatly raised by the Zylalabs Face Liveness Check API. Because of one of the best biometric anti-spoofing algorithms currently available, our clients successfully avoid identity theft.
The identification of facial features in any image or video is made possible by face recognition technology, which employs biometric authentication methods. The face is recognized using the picture and the official documentation that your clients have given. For authenticity, it incorporates a variety of AI-powered methods, including liveness recognition, depth mapping, skin texture analysis, and 3D sensing.
Just take two images of the same face with an ordinary camera, looking for variances and natural movements. Our sophisticated algorithms for motion analysis can detect the distinctive facial movements.
We can identify presenting threats like 3D masks, replayed videos, projections, etc. thanks to APIs that employ artificial intelligence.
To recognize video replays and other imitations, such as avatars or deepfakes, we employ a particular texture-based method. When a simulated image of a person rather than the real thing is displayed, it is aware of this.
We can ask the user to turn their head in a specified, randomly chosen direction, and then verify that the head indeed did turn in that direction (challenge-response liveness check).
Live shot photo API produces even greater degrees of security and counters replay attacks. The simultaneous recording of multiple biometric characteristics, such as facial recognition and eye/periocular measurements, can be coupled in a variety of ways depending on the circumstance and the desired level of security. When numerous biometrics must be supplied at once, it is significantly more difficult for an attacker to pull off a successful fraud. The person register would have select from a variety of biometric characteristics when authenticating, which provides another convenience. For instance, if you’re wearing a medical mask, you can decide to perform regularly.