Biometrics is an automated technology used to recognise persons using physiological identifiers. Biometrics covers a variety of technologies in which people’s unique identifiable attributes are used for identification and authentication. These include a person’s fingerprint, face, iris, voice, palm prints, which can be used to validate the identity of individuals. Biometric data are unique to each person, so they can be used in almost any application that requires accurate identification or verification of any individual

My-ID contains a facial identification system that does not require any advanced hardware, as it can be used with existing image capture devices ios and android smartphones, webcams, security cameras, etc.

Usually, these systems extract certain features from face images and then perform face matching using these features. A face does not have as many uniquely measurable features as fingerprints and irises, so the reliability of facial recognition is slightly lower than these other biometric recognition methods. However, it is still suitable for many applications, especially considering its convenience for the user. Facial recognition can also be used together with fingerprint recognition or another biometric method to develop more security-critical applications. The multi-biometric approach, followed by My-ID, is particularly important for (1-to-many) identification systems. In general, identification systems are very convenient to use because they do not require any additional security information (smart cards, passwords, etc.). However, the use of 1-to-many matching routines with only one biometric method may lead to a higher probability of false acceptance, which may become unacceptable for applications with large databases. The use of facial identification as an additional biometric method can drastically reduce this effect. This multi-biometric approach also helps in situations where a certain biometric characteristic is not optimal for certain user groups.

It offers fast and reliable identification with real-time face detection, the ability to process multiple faces in a single frame and fast face matching in 1-to-1 and 1-to-many modes.

The My-ID face recognition algorithm implements advanced face localisation, enrolment/enrolment and matching using robust digital image processing algorithms based on deep neural networks: Simultaneous processing of multiple faces. The face algorithm performs fast and accurate detection of multiple faces in live video streams and still images. – Gender classification. Optionally, gender can be determined for each person on the image with a predefined degree of accuracy during pattern extraction. – Real-time face detection. A conventional facial identification system can be fooled by placing a photo in front of the camera. The face algorithm is able to prevent this type of security breach by determining whether a face in a video stream is ‘live’ or a photograph. – Live detection :can be performed in passive mode, when the engine evaluates certain facial features, and in active mode, when the engine evaluates the user’s response to perform actions such as blinking or head movements.

My-ID optionally allows the estimation of a person’s age

My-ID allows for a minimum threshold of image quality