What are computer vision applications in biometric identification

Computer vision is a field of artificial intelligence where computers are programmed in such a way that they are able to perceive, interpret and analyze visual information from the surroundings.

Applications in biometric identification

The following illustration shows the applications:

Facial recognition

Such systems are programmed in such a way that they identify the facial features of a person. Computer vision plays a huge role in developing these models and helps verify a person's face that is used in security and access systems.

Retina and iris recognition

Retina and iris recognition systems are most commonly used in airports, where a person's identity is verified by scanning the iris (eye color) and retina (unique patterns of the blood vessels at the back of the eye) using computer vision models. These methods are highly accurate and are widely used in security systems.

Access control systems

At many places and businesses, specific access control systems are needed so that only authorized personnel/employees can be authenticated and allowed access. Computer vision widely helps in developing these systems for workplaces where access is appropriately allowed or denied.

Fingerprint and palmprint recognition

Fingerprint recognition is the most commonly used application of computer vision which is today widely available in almost all our personal devices and uses the fingerprint pattern to authenticate the person. This system is also used in workplaces. Palmprint recognition is similar to a fingerprint, which instead uses the unique patterns of palms to identify the person.

Border control and immigration systems

Similar to access control systems, computer vision helps in immigration systems where several computer vision models are deployed at checkpoints or airports to identify and authenticate immigrants/travellers and to deny any illegal or unauthorized entry.

Gait recognition

In gait recognition, computer vision algorithms are applied to extract information regarding how a person walks, which can help identify a person and their behavior.

Multi-model recognition systems

Many systems use combinations of several computer vision models for biometric identification. An example of this is the combination of fingerprint scanning and facial recognition feature that is most commonly available on our mobile phones.