Vision Mobile and Web SDK
Face recognition and liveness detection
Detecting a face or absence of faces in a photo
A real person in the photos, or a scammer with a photo, video or deepfake
JS and mobile SDK
For implementation in your application (face detection, detection of face rotation angle, detection of open/closed eyes, etc.)
TRUST ID is a client-side server system designed for facial recognition and various types of photo analysis.
- Detection of a face in a photo or its absence: The system uses a face recognition algorithm (Face Detection) to detect and highlight faces in the provided photographs;
- Comparing photos with data from the database: Using the 1 to N comparison algorithm, the system compares recognized faces with data stored in the database and determines the percentage of matches with each profile;
- Liveness detection (Определение живого лица): Для предотвращения мошенничества система использует алгоритмы для определения, является ли лицо на фотографии реальным человеком или статичным изображением, маской, видео или дипфейком;
Photo quality analysis:
- Photo blur: The system can analyze image blur, which allows you to evaluate the quality of the photo and its suitability for identification;
- Lighting and photo color: Lighting and color analysis algorithms allow you to take into account possible distortions due to shooting conditions;
- Eyes open/closed in the photo: The system can determine whether the eyes on a face are open or closed, which is also important for confirming a living person;
- Determining the angle of rotation of a face in a photo: The system can analyze the angle of rotation of a face in a photo, which helps in correct identification;
- Counting the number of people in the frame: Using object and face detection algorithms, the system can count the number of people in a photo;
- Probability of a photo belonging to a specific person: The system can estimate the probability that a photo belongs to a specific person based on comparison with records in the database;
- Custom settings: The user can configure photo comparison thresholds, acceptable blur, light, color and other parameters depending on their needs.
- Face detection: Face detection algorithm is used to detect the face in a photo;
- 1 to N (1 to N) comparison: The algorithm allows you to compare recognized faces with a database to identify matches;
- Liveness detection: Liveness detection algorithms help prevent fraud;
- Comparison: The system can use comparison algorithms to evaluate the similarity of photos and compare the data with the database.
This system provides a high degree of accuracy and reliability in identifying and analyzing faces in photographs, making it a useful solution for a variety of applications, including customer and employee authentication, and security in a variety of applications.