There has been rapid growth in technologies, but this digital world also has to face a number of crimes on a daily basis, such as identity theft and financial scams. Hackers are really active now to take advantage of this modern digital world.
As per the report, in 2022, 286,890 identity theft cases have been noted for a special age group only. Therefore, an advanced solution is required to make onboarding secure. Biometric facial recognition technology uses AI and Machine language-based models that work exceptionally fast. Facial biological features are detected with the help of AI-based face scanners that reduce the risk of identity theft.
How Does Facial Recognition Work?
Machine learning algorithms work behind facial recognition solutions, which can compare a captured image with a database containing face prints. There are 80 nodal points on the human face. These points are used to store face prints in an electronic database.
As per the report, the National Institute of Standards and Technology claimed that the usage of facial recognition systems has been twice in number every two years since 1993. The face recognition process works as follows:
- Face Detection
- Face Analysis
- Conversion
- Database Match
Face Detection
An individual has to encounter the camera and the image is caught. Face scanners are very sharp; they can even detect a person’s face in a crowd. All the features are captured by the scanner within seconds.
Face Analysis
Both 2D and 3D pictures are identified by face recognition technology. 2D images are effective when compared with digital databases. Once a face is captured, the face recognition deep learning process begins. In this process, facial geometry is analyzed. Facial geometry contains various biological features such as the depth of the eye socket, the distance between the chin and forehead, the contour of the chin, lips, ear, cheekbones shape, and skin tone. These facial features are analyzed to identify a person’s identity.
Conversion
The scanner captures facial images as analog data. This data is converted into digital form. Here, the facial analysis is turned into mathematical formulas and digital data is stirred as face prints. Every individual possesses unique face prints.
Database Match
Face prints are compared against the database of another already saved face. Whenever an individual has to undergo a biometric facial scan verification, these face prints are matched with already stored information, hence a successful verification is done.
Benefits of Biometric Face Recognition
Removed Biasness
Automated face scanners work along with machine learning algorithms, which are unbiased in the choice of identity verification. So there is no risk of any kind of negligence or favoritism due to advanced AI tools.
Accuracy
Machine learning algorithms are very sharp and efficient, eliminating the risk of identity theft. Every individual possesses unique facial features that are easily identifiable with the help of automated face scanners with accurate results. Manual work may generate inaccurate results for a person’s subjectivity.
Fast Processing
Biometric face scanning takes only a couple of seconds. It has reduced cyber attacks. Companies use biometric face scans to have quick and efficient identity verification.
Contactless Verification
In fingerprint verification, a person has to be involved in physical contact, and if there is dirt on the thumb, verification would be difficult.
Use Cases of Face Recognition
Although biometric face scan has helped industries worldwide. The top use cases of face recognition are the following:
Unlocking Phones
Biometric face recognition is used in various gadgets to protect personal data. Moreover, data remains inaccessible if the phone is stolen.
Education Sector
Education institutions are using biometric face scanners at the entrance for student and staff attendance.
Airports and Border Control
Airports issue biometric passports, which allow facial verification. Thus passengers don’t need to stand in line and they reach the gate faster. Face recognition not only eliminated waiting time but enhanced airport security as well.
Online Banking
It allows customers to have quick transactions instead of using one-time passwords. Biometric facial recognition allows banks to prevent money laundering.
Key Takeaways
Biometric facial recognition technology is used by organizations to prevent the risks of fraud and identity theft. It is a very fast and accurate solution to overcome the issue of identity theft. Every individual has unique biological features, these are verified to access a person’s identity. Advanced Machine learning algorithms work along with biometric face scanners to provide fast and accurate identity matches. It reduced the ratio of cybercrimes and made organizations safe. Biometric facial recognition allows genuine customers to be onboard.