Developed by Oz Forensics specialists, the biometric module incorporates the latest practices in artificial intelligence and is consistently improved by continuous data enrichment. The face recognition algorithm from Oz Forensics achieved one of the best test results in accuracy on the LFW dataset in University of Massachusetts tests in 2020 MIT LFW. The Oz Biometry module allows identifying people with less than 1-second speed and 99.87% accuracy.
Since the beginning of the 2010s, every smartphone has a front camera, making facial biometrics a natural way for authentication. Face biometry can be used both in the registration process and in the process of searching and authentication on large biometric databases.
Facial biometrics are used in the KYC process to compare selfie photos with photographs from documents and confirm the presence of a user in biometric “black” and “white” lists.
Oz Forensics Face Recognition Algorithms allow:
- Detect and highlight the best shot from the video;
- Compare face from photo with face photo from ID;
- Perform a search in the biometric database.