Facial recognition is defined as any system that can recognize an individual based on a visual representation of his face, such as a photograph, video, or audio recording. This kind of identification is typically used in conjunction with a biometric scanner, like a face scanner, to get access to a restricted area or resource.

In the context of biometric identification, it refers to a technique that utilizes an individual's facial biometric pattern and data in order to confirm their identity. The system collects a set of distinctive biometric data about a person's face and facial expression in order to identify, verify, and/or authenticate that individual.

Facial Recognition Software

Any device that is equipped with digital photographic technology can be used to carry out the face identifier method. As a result, the system will be able to generate and collect the information needed to create and save the biometric face pattern of the person who needs to be identified.

The fact that biometric facial recognition uses one-of-a-kind mathematical and dynamic patterns and functions as a face scanner, in contrast to other methods of identification such as passwords, verification by email, selfies or photos, or fingerprint identification, makes this system one of the most reliable and efficient options available.

The goal of face recognition is to, given an image as input, locate, among a collection of training photos stored in a database, a number of instances of the same face that correspond to the input image. The greatest challenge is making sure that this procedure is carried out in real time, which is something that is not available from all of the companies that make biometric face recognition software.

How does Facial Recognition work?

The widespread usage of Face ID to unlock iPhones has brought widespread attention to facial recognition technology, but this is just one of many potential uses. Facial recognition can work without access to a massive image database because all it has to do is confirm the identity of the device's sole owner and prevent anyone else from using it.

  • Step 01: Facial detection

The camera is able to recognize and localize an individual face even when there are other people present in the frame. It's possible that the person is seen staring straight ahead or in profile in the picture.

  • Step 02: Facial analysis

The next step is to take a picture of the person's face and analyze it. The majority of facial recognition technology works with two-dimensional images rather than three-dimensional ones because it is simpler to match a two-dimensional image with photographs that are already in a database or that are in the public domain. Your face is analyzed in terms of its geometry by the software. The distance that separates your eyes, the depth of the eye sockets, the length of your face from your forehead to your chin, the form of your cheekbones, and the contour of your lips, ears, and chin are all important aspects to consider. The purpose of this exercise is to locate the facial landmarks that are essential to recognizing your own face.

  • Step 03: Converting the image to data

The "face capture" technique turns an analog piece of information (a face) into a collection of digital pieces of information (data) by utilizing the person's distinctive facial traits. Effectively, a mathematical formula is created from a study of your face. A face print is the name given to the numerical code. Each individual possesses their own one-of-a-kind face print, much in the same way that thumbprints are singular.

  • Step 04: Finding a match

After that, a database of other known faces is compared to the faceprint that you provided. The FBI, for instance, has access to as many as 650 million photographs that have been taken from a variety of state databases. A person's name gets entered into Facebook's database, which can be used for facial recognition, when it is added to a photo. This applies to both public and private photos. A conclusion can be drawn about your identity if your faceprint is compared to an image in a database that has facial recognition information.

Facial recognition is regarded as the most natural form of all the different types of biometric measures. When you stop to think about it, this makes perfect sense considering how much more often we remember ourselves and other people by their faces than by their thumbprints and irises. It is estimated that more than half of the people in the world are routinely interacted with by technologies that utilize facial recognition.

Use of Facial Recognition

The technology is put to work in a wide variety of contexts. The following are some of them:

Unlocking phones

Face recognition may be used to unlock a variety of mobile devices now, including the most recent iPhone models. If a phone is lost or stolen, the important information will still be inaccessible thanks to the technology, which provides a robust method for protecting personal data. Apple estimates that the likelihood of your phone being unlocked by a stranger's face is approximately one in one million.

Law enforcement

Law enforcement agencies frequently make use of facial recognition technology. According to a story that was broadcast on NBC, the prevalence of the technology is growing among police enforcement agencies in the United States, and the same can be said for agencies in other nations. The police take mugshots of those who have been arrested and compare them to facial recognition databases kept at the municipal, state, and federal levels. When a photo of an arrestee is taken, it is entered into databases and examined each time the police use those databases to perform another criminal search.

A snapshot of a driver or pedestrian can be swiftly compared with one or more face recognition databases using mobile face recognition, allowing law enforcement officers to use cellphones, tablets, or other portable devices.

Airports and border control

At a growing number of airports all over the world, facial recognition technology has established itself as a common fixture. A growing number of passengers are in possession of biometric passports, which enable them to bypass the typically lengthy lines and instead pass through an automated ePassport control in order to reach the gate in a more expedient manner. Not only can facial recognition cut down on wait times, but technology also enables airports to tighten their security measures. Facial recognition is expected to be used on 97% of travelers by the year 2023, according to the Department of Homeland Security in the United States. In addition to being utilized to improve safety at airports and other checkpoints, this technology is also put to use to bolster protection at large-scale events such as the Olympics.

Finding a missing person

It is possible to locate missing persons and victims of human trafficking with the help of facial recognition technology. Imagine that a database is updated to include people who were previously absent. In this scenario, police can be notified as soon as the suspect is identified using face recognition technology, regardless of whether the incident took place in an airport, a retail store, or some other public place.

Reducing retail crime

Face recognition technology can be used to recognize known shoplifters, organized retail criminals, and anyone with a history of fraud when they enter establishments. Loss prevention and retail security experts can be alerted when customers who could potentially pose a threat enter the store when their photographs are matched against huge databases of known criminals. Photographs of individuals can be compared with vast databases of known criminals.

Improving the retail experience

The application of this technology has the potential to enhance the shopping experiences of end users. For instance, self-service kiosks in retail locations might identify customers, provide them with product recommendations based on their previous purchases, and point them in the correct direction. The technology known as "face pay" may one day enable customers to bypass the lengthy checkout lines that are associated with more cumbersome payment options.


Another advantage of using facial recognition is that it can be used for biometric internet banking. Customers are able to authorize transactions without having to use one-time passwords by simply looking at their smartphones or computers to do so. When using facial recognition, there is no need for a password, which means that it is much more secure. In theory, 'liveless' detection, a technique to assess whether the source of a biometric sample is a live human being or a phony representation, should prevent hackers from exploiting your photo database for impersonation if they manage to get their hands on it. If a biometric sample comes from a real person or a fraudulent depiction of one, it can be determined using the technique of "liveless detection." Face recognition technology has the potential to replace debit cards and signatures.

Marketing and advertising

Facial recognition is being utilized by marketers to improve the overall customer experience. For instance, the frozen pizza business DiGiorno employed facial recognition for a marketing campaign in 2017 in which it examined the facial expressions of participants at events themed around DiGiorno in order to determine how people felt about pizza emotionally. Facial recognition software is also utilized by the media industry to gauge audience response to movie trailers, characters in television pilots, and the optimal placement of television advertisements. Face-recognition technology embedded on billboards, like the kind found in London's Piccadilly Circus, enables companies to send customers specific ads that are relevant to them.


The use of facial recognition technology in hospitals is intended to improve patient care. Facial recognition technology is now being evaluated by professionals in the medical field for a variety of applications, including accessing patient records, streamlining the patient registration process, determining whether or not a patient is experiencing emotion or discomfort, and even assisting in the diagnosis of some genetic illnesses. AiCure has created an app that makes use of facial recognition technology to monitor whether or not patients are taking their medication as directed. It is anticipated that the adoption rate of biometric technology within the healthcare sector will increase as the costs associated with this technology decrease.

Tracking students or workers attendance

Face recognition technology is being implemented in some of China's educational institutions to prevent students from bunking classes. Tablets are utilized to perform face scanning on pupils, after which their scanned images are compared to photos stored in a database to verify their identities. In a broader sense, the technology can be utilized by workers to check into and out of their workplaces, enabling employers to keep better tabs on employee attendance.

Recognizing drivers

This consumer research suggests that automobile manufacturers are exploring the possibility of using facial recognition software in place of traditional car keys. The technology would be used instead of a key to access and start the vehicle, and it would remember the preferences of the driver about the position of the seats and mirrors, as well as the radio station presets.

Monitoring gambling addiction

Gambling establishments can provide a higher level of security for their patrons by using facial recognition technology. It is difficult for human workers to keep track of people who are entering gaming areas and moving throughout such areas, particularly in huge, busy locations like casinos. The use of facial recognition technology gives businesses the ability to detect customers who have been documented as gambling addicts and maintain a record of their gameplay so that employees may provide guidance regarding when it is appropriate to call it quits. If gamblers who are on voluntary exclusion lists are detected gambling at a casino, the casino could be subject to heavy fines.

Using biometric templates on personal devices

As a verification or client onboarding tool, biometric authentication is now employed on personal devices rather than a personal identification number (PIN) or is built-in within an application. However, the most important reason why manufacturers of mobile phones employ it is because of its convenience. There is no requirement for management or protection via passwords. In addition, both fingerprint and facial recognition are far quicker than more conventional means of verification. There is also an increase in security due to the fact that your password cannot be easily stolen by anyone simply looking over your shoulder. Last but not least, the user can be certain that no one else is tampering with the data because there is technology that matches devices, the data is never shared with third parties, and it is not stored on the cloud.

Ethical issues in using Facial Recognition Technology


1. Racial bias due to testing inaccuracy

One of the primary concerns regarding facial recognition technologies is still racial bias. Facial recognition algorithms have a categorization accuracy of above 90%, although this isn't always the case. Recent developments have raised fresh questions about the ethics of facial recognition systems. Nearly 117 million Americans, or more than half of the adult population, have images in law enforcement's facial recognition database. Uncomfortably, the face recognition algorithm made more mistakes when identifying dark-skinned faces than when identifying light-skinned individuals.

2. Racial discrimination in law enforcement

Recently, the US government admitted that its facial recognition technology has discrimination issues. People of color, the elderly, women, and children fared poorly under this method, but middle-aged white men's looks fared well. These racially discriminatory, clumsy algorithms can result in major issues including erroneous arrests, lengthy jail terms, and even police brutality.

3. Data privacy

Unsafe methods of storing data raise privacy concerns with regards to facial recognition because sensitive information could be compromised. Because of security risks and a dearth of IT security experts, most companies still store their facial data on internal systems.

When stored in the cloud, facial recognition technologies add an extra layer of safety to protect sensitive information. However, good encryption is the only way to ensure data integrity. Deploying IT security employees is crucial for safe data storage, user agency, and the mitigation of hostile traffic.

4. Lack of informed consent

Even though the majority of data obtained online is anonymized, data mining still raises privacy concerns. Facial recognition algorithms can be tested and trained using large datasets of images, ideally amassed in a variety of lighting conditions and camera angles.

Online sites, particularly public Flickr photographs submitted under copyright licenses that allow for liberal reuse and occasionally questionable social media platforms, are the most common places to find images.

In 2019, these and other statistics were highlighted on the website MegaPixels, created by Berlin-based artist Adam Harvey. Along with technologist and programmer Jules LaPlace, he demonstrated that the vast majority of users had provided unrestricted access to their uploaded images. In reality, however, they were being used in an effort to improve the quality of commercial surveillance devices.

In Conclusion

The development of reliable facial recognition technology is no longer theoretical. It's already here, and many businesses are adopting FRS for safety, promotion, and other uses. FRS's analytic brilliance can be put to use in predictive research and product improvement. Businesses should put each FRS solution through rigorous testing using a realistic dataset before deploying it.