Facial recognition technology has become an essential process for industries to streamline their safety and security measures. Financial and banking platforms use facial recognition to authenticate their onboarding customers to provide them access for performing transactions. It also reduces human resources and the time required for manual verification. Face recognition cameras are used by security enforcement agencies for the surveillance of criminals. Introduction
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What Is Face Recognition Online?
Face recognition online refers to a process to verify the identity of an end-user by matching his face image with other facial image templates in the database. Facial recognition technology uses machine learning algorithms to extract the unique facial features of the end-user and convert them into machine-readable code. Unique facial features include the distance between the eye sockets and the shape of the chin.
How Client Face Verification Is Performed?
Face recognition online is one of the fastest and robust biometric technologies used for the authentication of human faces. The machine learning algorithms of facial biometric verification follow different steps of digital image processing techniques that are given below:
- At the start of the process, the sample of the end user’s facial features and gestures are collected during the given time interval.
- After the collection of the sample, the sample is extracted for creating templates based on the end user’s facial features.
- After templates are created, they are matched against other templates in the database.
- In the end, the facial recognition technology determines whether the new template matches any previously saved samples in the system database.
Pros Of Face Recognition Technology
Occasionally, the facial recognition mechanism works perfectly with the existing safety mechanism that enterprises have deployed. And they are easily programmed for interacting with the enterprise’s computer system. Why is it beneficial for companies? Companies won’t have to waste their time and money on rebuilding their own software to make it appropriate for the integration of facial recognition mechanisms. It will have the ability to adapt easily.
Nowadays, facial recognition technology is becoming more successful and widespread than before. With the help of 3D depth perception and liveness detection features the identification process has become highly accurate and delivers better results. It is difficult to bypass this system. Accuracy ensures that there will be no misunderstandings that usually occur in bad facial recognition mechanisms.
Facial recognition is a better alternative to fingerprint scanning. It doesn’t need any contact procedure for verification. People don’t have to be anxious about the defects related to fingerprint verification technology, which include dirty hands.
Secure and Robust
With the rise in demand for speed and rapidly increasing cyberattacks, the adoption of a robust and swift mechanism is vital. A facial recognition solution ensures swift and highly accurate verification. It is very hard to trick the face recognition mechanism, that is why it prevents fraud.
Usually, Security guards or bank employees perform manual verification of customers. On the other end, facial recognition automates the verification process and ensures that it remains frictionless each time. The deployment of more human resources and spending high costs for manual verification are not required. As facial recognition reduces expenses while providing convenience.
Cons Of Face Recognition Technology
It needs a high cost for the deployment of advanced software and high-quality cameras that are quite expensive. But with the passage of time and technological advancements, it is expected that the cost of facial recognition technology will reduce.
Huge data Storage
High-resolution images and videos require a large amount of storage. Companies use many computers to process images and videos, which is inconvenient.
Camera Angle and Appearance
A significant change in appearance such as weight loss makes it difficult for the face recognition system to verify his identity. To solve this problem, a recent picture of the end-user is required as technology fails to verify the previously saved facial image. Camera angle also causes an issue in the identification of the face.