A few years ago, biometric technology potential was illustrated in different Sci-Fi films, which amazed audiences with AI advancements that seem unattainable in the real world. With time, biometrics has emerged and found general applications in everyday life. These technologies continuously evolve, improving safety and convenience. 

 

AI biometric technology is employed for tasks like opening smartphones, using two-factor authentication to access accounts, and making secure payments. Its prevalence has become so common that it is usually taken for granted. This trend has led professionals to predict the global biometric verification and identification market will reach $99.63 Billion by 2027. 

 

Facial verification has gained significant popularity across various industries as a biometric tool, primarily due to its exceptional security capabilities and remarkable efficiency. Growing demand for a face verification system accounts for an accuracy rate.

Understand Everything About Facial Verification 

Facial verification is an AI-based solution for face identification and recognition. The software detects the user’s eye shape, nose parameters, and forehead length and compares them with the information previously provided by individuals. If a face verification system encounters a match in a database, it verifies an individual’s identity. Face matching can be executed through videos or images and in real-time. 

 

This technology has demonstrated its credibility in face analysis, specifically in identifying user characteristics that help detect individuals who violate the regulations of wearing masks in public areas. Such factors include age, gender, emotions, mood, face mask, and movements. 

 

Unlike authentication methods such as emails, fingerprints, and passwords, face scanning applies mathematical equations and unique dynamic patterns that ensure the efficiency of a face detection system. 

 

Face verification systems experience large-scale applications in different spheres such as e-commerce, retail, entertainment, media, transportation, automobile, etc. 

 

Now, let’s explore how the online face verification system works. 

Main Steps Involved in Facial Verification Technology 

Facial recognition stands out as a remarkable advancement in biometric technologies, bypassing all others. AI facial technology interprets it as useful data whenever a face is encountered. This data experiences a series of steps to confirm and validate the identity of a user. 

  1. Detecting a Face

The primary stage in facial recognition is the face detection procedure. During this step, the software scans the image to recognize areas that contain partial or complete human faces and facial features. This stage is vital in the complete process, as the technology accurately or swiftly detects a face, whether it emerges among a group or alone. 

  1. Extracting Facial Features 

Face recognition services analyze the facial geometry of a user, including features such as the spacing between the eyes, the shape of the eyebrows, and more. In short, the software can recognize almost 70 specific facial landmarks. After extracting these traits, the software generates a unique template of the face and then compares it with the information stored in the database. 

 

  1. Recognizing a Face 

At this stage, the facial recognition software carries out the verification and identification process. Verification is executed when there is a requirement to authenticate a user’s identity. In this process, the face recognition software compares a faceprint obtained in the previous step with the existing data to know if they belong to the same user. 

 

This process verifies or denies the claimed identity by assessing the similarity between the two faceprints. For example, this verification step usually happens while unlocking a mobile phone or logging into any banking portal for financial services. 

 

The second process aims to identify an individual based on their claimed identity. After doing so, the software automatically searches the database of pre-registered faceprints to find a perfect match for the user’s faceprint. 

Facial Recognition with Edge Computing

Both edge-based, and cloud computing technologies are used for deploying face scanning. While every method provides various advantages, edge-based facial recognition becomes increasingly famous due to its essential characteristics. These characteristics include excellent security, flexibility, affordability, and versatility.  

 

In cloud computing, facial recognition information is processed in a centralized cloud data centre far from the user. While on the other hand, edge computing enables data processing on devices situated at the network’s edge. 

 

This method provides the benefits of reducing the need for an internet connection and the risk of security breaches. Edge devices like interactive kiosks, smartphones, smart locks and POS systems can accurately and quickly identify faces without depending on a distant cloud server. 

 

Key Takeaways 

Facial verification is a highly efficient and widely adopted biometric technology in different industries. Its applications range from smartphone unlocking to safeguarding payments and account authentication. 

 

Facial verification technology has transformed how companies authenticate and recognize users, offering a convenient and secure solution in different domains. Its constant advancements and increasing adoption pave the way for a future while biometrics is crucial in improving safety and convenience in our daily lives. 

By ouns

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