Infrared dots are used in the latest facial recognition technology that creates a face mapping in the database that is further used for real-time identification. Moreover, it enables security in accessing some device or online application.

Facial authentication helps ensure controlled access over the user accounts.

Biometric login is used almost by all industries for the purpose of online security such as online financial services portals, stock exchange platforms, the gaming industry and even in the healthcare and education sector.

Facial Recognition Technology is empowered by Artificial Intelligence (AI) algorithms and techniques that help build robust security platforms. Online systems are designed in such a way that they help prevent spoofing elements in the facial proofs to unlock the accounts and devices.

A couple of other authentication methods such as two-factor authentication, password authentication, email authentication, etc are not strong enough to fight against fraudulent attempts. Biometric identification is popular because of the unique identifying information of individuals that are used to authenticate and differentiate an individual from the other.

Unlike other authentication methods, the user does not need to remember passwords or pass through the overhead of verifying identity by conducting several actions. Instead, face verification is done just by capturing the facial features of an individual in real-time and authenticating them against some identity proof such as ID card or against the previously-stored facial information present in the database.

Techniques Used in Face Recognition Technology

Facial recognition techniques and algorithms identify unique facial features by extracting some landmarks from the face image of a subject. For example, face size, relative position, the shape of eyes, cheekbones, nose, and jawline. These features of every person are also used to test facial recognition models.

Following are some of the techniques used in facial recognition technology:

Liveness Detection

In face recognition, the liveness detection technique is used to ensure the physical presence of the online user. In this, minor facial movements of a person are analyzed using AI algorithms that help prevent the printed image or photoshopped image spoofing attacks.

3D Depth Analysis

Emerging trends in facial recognition software use 3D depth analysis n which a 3D model of the face is created. The distinctive facial features are analyzed especially where bones and rigid tissues are apparent. For example nose, eye socket, and chin, etc. the distance between facial features is calculated for better identification and all this forms a 3D model and stores it in the database in the form of a mathematical formula.

Skin Texture Analysis

Face verification technology uses some other visual details in which skin texture is checked when captured in scanned images. The captured details such as unique lines, spots, and patterns are analyzed in a person’s skin and stored in the form of a mathematical model.

Afterward, the real-time captured facial information is checked against the previously-stored information with some precision rate that allows approximate values nearly equal to a stored mathematical formula.

Facial Recognition – A win-win for Online Businesses

Businesses can ensure the online security of their platform by allowing controlled access over confidential accounts. Not only in an online environment but also in place Know Your Customer helps deter the risks of various fraudulent activities. Malevolent actors and their malicious purposes can be prevented by allowing authorized access.

Moreover, other benefits of facial recognition technology are that the percentage of data breaches and identity theft cases can be reduced by identifying each onboarding against unique facial features. Based on Artificial Intelligence algorithms and underlying sophisticated functionalities, facial recognition technology is gaining ground in this digital globalized era.