Facial Recognition

Facial recognition is a way of identifying and confirming a person’s identity through their face. It’s a form of biometric verification; other types of biometric verification include iris, retina, and voice recognition. Facial recognition is a system used to identify a person through photos, videos, and in real time. The technology collects unique data about a person’s features to authenticate their identity, which no one can hide or steal.

A biometric facial recognition system uses dynamic and mathematical patterns as a face scanner. This makes the system safe and reliable.

Where Is The Facial Recognition System Used?

The facial recognition system operates in two steps, depending on when it is performed.

• In the first step, the facial recognition system captures the face and associates it with the identity recorded in the system. This process is known as digital onboarding with facial recognition.
• In the next step, the incoming data from the camera crosses over with the existing data in the database. If the face matches the already registered identity, the user is granted access to the system with his credentials.

How Does Facial Recognition System Work?

A face recognition system uses a combination of hardware and software to capture an image in a two-dimensional or three-dimensional way for identification. The following steps explain how a face recognition system typically works.

Capture

This step involves capturing an image or video frame containing a person’s face. This can be done with a smartphone, camera, or other scanning device used for this purpose.

Pre-processing

The captured image is then preprocessed to enhance image quality and extract the relevant data for verification. This step is also used for normalization, alignment, and voice reduction of a picture or video to get the desired results.

Feature Extraction

In this step, the system analyzes the preprocessed image to extract unique facial features required for face authentication. Various techniques can extract facial features, like local binary pattern (LBP), principal component analysis (PCA), deep learning-based approaches, etc.

Feature Encoding

The extracted facial features are encoded into a numerical expression, which helps compare and facilitate efficient storage.

Database Comparison

The extracted facial template is compared against the database of known faces. The database contains a template of employees or authorized users. In this step, the similarity is checked between the captured image and the records in the database.

Matching recognition 

The system matches the template with the template in the database using a matching algorithm. The matching algorithm analyzes the similarity index and the distance metrics between the templates to determine the degree of resemblance. If the similarity index crosses the threshold limit, the user can access the system.

Decision and output

Based on matching results, the system generates an output indicating the identity of a recognized person. The output can be used for various purposes, such as identity verification, access control, and attendance records.

Biometric Facial Recognition Uses

Face identity recognition focuses on identification or authentication. This technology is used, for example, in cases such as

• Second authentication factor to add extra security to the login process
• Access to mobile applications without a password
• Access to buildings (offices, buildings, schools, etc.)
• payment methods
• Check in tourist activities (airports, hotels)
• Access to locked places
• Apple: uses this feature to facilitate their users ability to log in apps quickly and make purchases
• British Airways uses facial recognition for passengers boarding flights from the U.S. Traveler faces can be verified by the camera to confirm their identity so they can board flights without checking their passports or boarding passes. The process is convenient and time saving for a large number of travelers.
• McDonald’s uses facial recognition technology in their Japanese restaurants to check the quality of customer service. The technology is used to check whether the employees were smiling while dealing with customers or not.

Benefits of Facial Recognition

People occasionally ponder the advantages of machine learning facial recognition. A facial recognition system offers a variety of benefits for remote identification

The Fastest Process

The facial recognition system provides fast and smooth remote identity verification.

User Experience

Facial recognition offers a smooth, unique, and fast user experience.

Security

Like voices and fingerprints, faces also have some unique features that no one can steal or copy.

Compliance

Facial recognition through video identification is the only method recognized as a standard for remote identity verification for high risk operations (opening bank accounts, signing contracts, etc.).

Facial recognition makes identity verification easy and time saving. This feature is used in various fields for identity verification.