Biometric face recognition is how to recognize and verify a user’s identity using their face. It quickly identifies applicants in videos, photos, or in a real-time world. Facial recognition is a type of biometric security, and other forms include fingerprint, voice, eye retina, or iris recognition. Moreover, this technology is used for law enforcement and security.
In 2022, the face recognition market was projected at almost $5 billion. Now, it’s reaching $19.3 billion by 2032. Therefore, facial liveness verification is used with AI to recognize individuals by scanning their facial features.
Biometric Face Recognition Working
Customers are usually familiar with face recognition to unlock Phones. Facial recognition does not depend on an image warehouse to determine a user’s identity. It just recognizes a single user as the owner of the technology but limits access to the others.
Besides unlocking phones, facial recognition compares the individual’s face walking past a special camera to the user’s pictures on a watch list. This checklist contains everyone’s image, including users who aren’t doubted of any misbehavior. These pictures can be collected from anywhere, including social media accounts. Almost 60% of US adults believe it’s acceptable for law enforcement agencies to utilize biometric facial recognition to reduce security threats.
Let’s see how facial recognition systems work:
- Face Detection
The camera inspects and identifies a face image in a crowd or alone. The picture actually shows the individual looking straight or in any other direction.
- Face Analysis
The next step is that the software captures and analyzes the user’s face. Usually, facial recognition verification technology depends upon 2D instead of 3D pictures, as it can easily compare 2D images with public snapshots or those in databases. The software scans the user’s facial expressions, such as distance from chin to forehead, contour of the ears, lips or chin, eye sockets depth, and distance between eyes. The primary goal is to recognize the facial landmarks that can easily discriminate against the user’s face.
- Convert the Picture to Data
The face recognition services revolutionize analog information into a digital one depending upon the user’s facial expressions. The software automatically turns the face analysis into a mathematical formula, and the numerical code is known as faceprint. However, in the same way, the thumbprints are unique and sometimes used for recognition.
- Find a Match
Face recognition solution providers compare familiar databases with others. For instance, the FBI can access more than 650 Million images from different databases. At Facebook, the picture tagged with a user’s name is a part of its database that can be used for recognition purposes. Target is achieved if the faceprint matches with pictures in the database.
Facial Recognition Verification Benefits
Almost 4 in 10 users don’t believe that firms can track employee attendance using advanced technology. Companies are surprised at how remarkably facial recognition software protects users’ personal data.
- Efficient Security
Facial recognition is an efficient, instant, and convenient verification system compared to other biometric technologies such as retina scans and fingerprints. There are some touchpoints as compared to PINs or entering passcodes. Hence, it supports multi factor authentication for security purposes. Moreover, it also protects its clients from imposters.
- Improved Accuracy
Face liveness verification is an authentic way to recognize users compared to verifying through mailing or IP address. For instance, most exchange services, from cryptos to stocks, depend on this system to secure clients and their digital assets.
- Easier Integration
Face recognition services are compatible and incorporated easily with security software. For instance, android phones with front cameras have built-in support for software code or facial recognition algorithms.
- Convenient to Use
The software provides easy use to skim through thousands of faces in a few seconds.
- Investigates Crimes
From police to law enforcement, biometric face recognition keeps checking on illegal or unwanted activities.
Importance of Facial Recognition
Iris or fingerprint algorithms need to be more accurate than facial recognition. Therefore, the accuracy of face recognition deep learning can be measured by two classes:
- False negativity
- False positivity
False positivity happens when the system wrongly considers images of two different users to be the same person. False negativity means that the software failed to investigate a similar individual. Hence, there is always a tradeoff between negativity and positivity; sometimes, setting the threshold is challenging.
Conclusion
Facial recognition verification predominantly uses AI, meaning passwords can be stolen or hacked, but not face print. Hence, it is safer than most authentication and identification strategies. Facial recognition accuracy varies due to external characteristics such as lighting, background, environment, hair, gender, liveness, and age. Moreover, the application of face recognition services is diverse and can be used by public bodies, governments, or financial institutions.
 and machine learning (ML) techniques to recognize and verify an individual.){kind=link}