There exist a healthy degree of uncertainty in understanding face recognition and authentication. In both of them, underlying technologies are different and are designed to address different purposes. Facial recognition technology got its viral element when Apple iPhone X launched. Embedded face lock is highly appreciated and fascinating for the consumers that it gave exposure to many other applications that can make efficient use of face recognition technology. 

Biometric authentication is serving various purposes at an industrial level. Hence making them more workable and streamlined with robust verification processes. Biometric verification works on extracting the unique biological traits of the human body that differentiate them from others. These include fingerprint scanning, face verification, iris/retina scanning, palm geometry, keystroke scan, etc. 

Face recognition involves the extraction of unique facial features based on face cuts, contour, and shape. This facial recognition information is stored in the database and for each onboarding identity, facial features are verified based on the stored patterns. Face recognition is a more admirable technology among all biometrics. Industries are leveraging their use on a wider scale.

Facial Recognition Industrial Applications

At an industrial level, the use of facial recognition technology is facilitating to deter the growing fraud rate.

Retail Industry: Facial recognition is helping the retail industry when fraudsters with fraud history enter into the premises of a retail sector and got caught by the facial recognition cameras which help in verification of identity.

Social Media: To cut the roots of fake identities in social media platforms, facial recognition is the need and is harnessed by many social networking platforms. This helps combat the fraud rate social media is exposed to.

Education: In the education sector, facial recognition is used for surveillance purposes. To verify identities that are exposed with respect to organization, facial recognition is used. 

Exposed identities may include expelled students, dangerous parents or entities that are harmful to the school. Through face verification, entities would be first verified and then allowed to enter school grounds.

Financial Institutions: In financial sectors, face recognition technology is used to conduct secure digital payments, registration of an online account and funds transfer. Banks and online insurance companies can take in place an online face verification solution to verify their identities online. This will help deter the risks of fraudulent activities that happen in banks. 

Travel Industry: Travel experience has never been this much streamlined. Face verification is facilitating tourists with about boarding. Now instead of standing in queues and waiting for the turn, through face verification online, passengers can book the seats and can verify themselves in seconds. American airports are taking advantage of face verification solution to verify passengers.

Surveillance Purposes: Police and investigation departments are inciting facial recognition technology. In the US, face recognition based cameras are installed in malles, streets and public squares to track criminals and monitor criminal activities. Through face verification, identities are identified and verified that is helping police in tracing and catching thieves. 

Steps, How Facial Recognition Works

In facial recognition, a human face is verified through underlying algorithms and technologies. Modern software use biometrics that map facial features captured from a photograph or a video. These features are matched with the information stored in the database. Following are some step, that shows how online face verification works:

Step#1: Face is captured from picture or video, it could be alone or captured from a crowd. 

Step#2: Facial features are analyzed based on geometry. For example, face contouring, face cuts, the distance between two eyes, etc. Based on this information, facial signatures are formed by algorithms used in facial recognition technology. 

Step#3: Facial signatures are then compared with stored information. This is basically a mathematical algorithm whose values are matched with stored valued.

Step#4: A decision is made after matching both the values. If values are equal, identity is verified based on the face geometry.

The facial recognition system gives precise and accurate results. It is a foolproof system that carries capacity for identifying spoofing attacks. It runs checks to verify that the image is by no means photoshopped or tampered. Also, liveness detection is done which makes sure that identity is physically present at the time of face verification. This feature caters to the issues of fraudulent behaviors that use printed pictures or masks to fool the software. Liveness detection, a user is asked to prove that he/she is present. This can be done by detecting eye blinking or minor facial movements. 

To conclude, facial recognition technology is widely adopted more than any other biometrics. Its use-cases and smooth usages are fascinating consumers and industries. This is the reason, that the digital world is introducing new algorithms and technological updates to make facial recognition system more accurate. Its applications can be seen in almost all the sectors in unexpectedly useful ways.