The Rising Trend of Face Recognition System: Applications & Advantages

Several types of biometric technologies are used to identify people based on their physical characteristics like voice recognition, face recognition, iris recognition, finger or hand geometry recognition, DNA matching, and more.

Among these, face recognition is one of the most popular biometric security mechanisms verifying and authenticating people based on their facial features.

Why Is Face Recognition System So Popular Today?

Face recognition systems enable a fast and secure way of identifying individuals in a contactless manner within seconds. This is a safe method in today’s time, considering the rapid spread of a virus through contact.

With advancements in computer vision, facial verification accuracy has improved in face recognition systems, and the acceptability rate is quite high. The popularity of face recognition systems is further supported by their high image processing speed and ease of deployment.

Face recognition has multiple benefits in different areas like prevention of crimes by identifying offenders, attendance tracking of employees, etc.

Last year, the Indian government approved the deployment of the Automated Facial Recognition system (AFRS), the world’s largest government-operated facial recognition system, to identify past offenders from their faces in videos/ CCTV footage by matching against National Crime Records Bureau (NRCB) database.

In addition, in March this year, Walt Disney World employed a facial recognition park entry procedure for touchless entry and to cut waiting times.

What Is Face Recognition System?

A facial recognition system is a technology that uses algorithms for identifying or confirming a person’s identity via their photos, videos or in real.

A face recognition device uses an AI model face recognition software trained by providing various categories of different faces such as those based on race, ethnicity, gender, age and so on.

Where Face Recognition System Is Used?

Face recognition systems are used by private, commercial, government and law enforcement agencies. According to a report from the market research and consulting company Grand View Research, the global facial recognition market is estimated to grow exponentially with a compound annual growth rate of 15.4% from 2021 to 2028.

Some of the common uses of face recognition systems include:

• Law enforcement

  Face recognition systems help in reducing crime and increasing security radically. Law enforcement agencies worldwide store pictures of arrestees that are compared for future criminal searches.The image of any suspect can be captured in smartphones, tablets, and other devices on the go for comparing against database images. They can also help in finding missing persons and victims. The staff can be alerted when they are spotted in any public area.

• Retail services and shoplifting prevention

  There are payment systems that can help customers quickly buy items via facial recognition. Security personnel can be informed timely when a potential threat like habitual shoplifters and other criminals enter the store. Other things like personalized recommendations by recognizing customers help in improving the retail experience.

• Airports

  Many airports across the world are using facial recognition systems to reduce waiting times and ensure better security. In addition, many people have biometric passports which can be used for automated recognition.For instance, a self-service checkpoint was installed in 2020 at the Ronald Reagan Washington National Airport in Washington, D.C, where passengers can insert their IDs into a scanning machine. The machine also takes a facial scan to match the ID photo and confirm flight information within seconds.

• Banking

  Instead of using one-time passwords (OTPs) for transactions, face recognition systems prevent identity theft and enable fast transactions without any complicated process. It can also eliminate the need for loyalty cards, credit cards, or wallets.For example, Bank of America uses facial recognition on its mobile app, CashPro Mobile. It was granted a patent for a facial recognition authentication system in 2019. Other banks like HSBC and Chase use Apple’s FaceID to allow customers to log in to their mobile banking apps.

• Driving

  Many automobile manufacturers are adding facial recognition systems to identify vehicle owners, alerting them if they are not focused and playing their preferred radio stations.The new 2021 Cadillac XT4 for the Chinese market comes with a Face ID system installed in the front door frame. Another example of a built-in face recognition system is Buick Electra, reinvented as a concept car.

• Employee attendance

  Face recognition technology is often used at workplaces to help employees sign in and out. This way, employers can track attendance and authenticate employees. Further, attendance systems in schools use facial recognition to identify students who are attending a class.

• Phone unlocking

  Several smartphones available in the market use a face recognition system to restrict other people’s access to an individual’s personal data. In addition, companies like Samsung provide the option to delete face recognition data anytime also.

• Marketing and advertising

  Many companies use facial recognition systems to analyze people’s reactions towards different products based on their facial expressions. Big brands can even use it for personalized advertisements.For instance, Expedia Group Media Solutions partnered with the Hawaiian Tourism authority to create a personalized travel experience for their Hawaii-bound travelers.By determining the emotions via face recognition that images of the various travel itineraries and spots in Hawaii invoked, they identified what resonated with a website visitor the most.

• Patient information

  Patient health records and other information are confidential and must be accessed by authorized individuals only. Face recognition systems can also be used to detect pain or identify certain genetic diseases.One such example is the Face2Gene phenotyping app used by clinicians to detect rare genetic conditions like Cornelia de Lange syndrome.

What is Face Recognition Software?

Facial recognition software is an application that uses artificial intelligence technology to detect, analyse and recognize the particular face prints from the pre-existing database. It is widely used in smartphone applications, GPS tracker, facial biometric attendance, etc.

Related Categories: Biometric Device |Payroll Management Software | Attendance Management Software | Leave Management Software

How Do Face Recognition Software Work?

Face recognition software understand and analyze the input given to them in the form of analog information. The following are the main steps:

• Face detection

  Facial recognition systems scan a person’s face via mobile phone cameras with a Face ID feature or special cameras installed in private or public areas.

  The face of a person or multiple individuals in a crowd are detected in the camera view. The person can be looking straight at the camera or be at a different angle concerning the camera.

• Facial analysis

  The comparison of captured face images is done in 2D against public photos or those in a database. Face recognition software uses computer vision to understand the geometry of a face.

  Feature-based identification is done based on facial landmarks like eyes and nose relative to the face and each other. This includes the distance between eyes, the shape of cheekbones, the perpendicular distance between forehead and chin, the outline of ears, and more.

  3D techniques use 3D sensors to identify an individual with different poses, lighting, and expressions. This data is unique to every face and helps in differentiating faces. For real-time identification, depth of features is an important parameter to distinguish the person from their photo in front of a camera.

  The accuracy of results depends on how well the deep learning models are trained using massive datasets of images from cameras and videos to interpret and identify faces.

• Faceprint

  Like a fingerprint, a faceprint is a digitally recorded representation of a person’s face. A numerical code is generated after the facial information in the image is converted to digital data during facial analysis. This numerical code called faceprint is unique for every individual.

• Face recognition

  The faceprint is compared against a pre-existing database in the facial recognition system of known faces. The database may contain images of people from different sources depending on the purpose and user. In devices like mobile phones, comparison results match only with the owner to limit access.

How Does Face Recognition Software Transform Data: Case Studies

CaliBurger, a global fast-food restaurant chain, added facial recognition to the entry screening process last year. The faces of restaurant staff, delivery drivers and guests are scanned, and their temperature is noted. If a person has a fever, they are not allowed to enter. To avoid using a touch panel, customers are given the option to pay by registering for PopPay, a face pay service.

Facebook has been using the DeepFace facial recognition algorithm since 2010 to scan the faces of people in photos/ videos and offer suggestions about who that person is for tagging them. This is done based on the past photos of the user and the ones they have been in. Now, this feature is opt-in to ensure user privacy.

Smartphones from Apple, Samsung, Huawei, and several other manufacturers have face recognition features for unlocking phones. They scan faces using a 2D scanner and sometimes even an iris scanner for additional security.

Millions of British Airways customers have used face recognition technology to board flights without the need to present their passport or boarding pass at the departure gate over the years, thereby saving time. Finnair and Norwegian Air are other airlines that use facial recognition systems to verify the identity of traveling passengers.

Suggested Read: 10 Best Free & Paid Contactless Attendance System

How Does Face Recognition Attendance System Work?

A face recognition attendance system is a type of attendance tracker that uses facial recognition technology to verify the identity of individuals from its database and record their attendance based on the time of scanning.

It is contactless, unlike fingerprint-based biometric attendance. As a result, security and surveillance solution providers like Ramco Systems and Secureye have witnessed a hike in the number of inquiries about facial recognition systems. As a result, many companies have already replaced fingerprint-based attendance systems with facial recognition systems.

For face recognition-based attendance, companies have to upload employee data to the software. For example, employees can upload a clear picture of their faces.

Face attendance systems use a camera to capture an individual’s image. The face is detected and aligned into a bounding box. The analog information is converted into digital, and a faceprint is generated in the face attendance machine.

If the faceprint’s similarity index concerning images in the database is such that it matches a face, the person is recognized by the system. At this time, the attendance gets automatically marked, and the employee’s record with which the face matched gets updated. 

Based on the detection time, it will check if the face was captured by the camera earlier during the day. This determines the arrival and departure times.

Advantages of Face Recognition Attendance System: The Next Big Trend

Face recognition attendance systems use the face of employees to verify it against the company database and efficiently track the attendance of the workforce in real-time. The main advantages of using face detection attendance systems are:

• Better security and accuracy: Facial recognition systems identify the authorized staff in real-time and access those registered on the system only. Many attendance systems give accurate results with masks, skin aging, spectacles, and so on.

• Automated time tracking: Face recognition biometric attendance system can accurately mark each employee’s attendance, overtime, and absence. As a result, fraud with proxy attendance by swiping ID cards or signing on other’s behalf is not possible.

• Minimal error in attendance tracking: There are no manual errors, and companies can track exact employee hours. This helps save money.

• Curb the spread of diseases: To minimize contamination via physical contact, face recognition attendance systems can control workplace entry and exit.

• Easier implementation than other touchless systems: Face attendance systems are cheaper than other touchless systems as you can use a regular camera. Unlike iris recognition, where the users must stand still and may have discomfort, face attendance systems are easier to implement.

• Works on the go: No extra setup is needed. Remote or roaming staff can use tablets or mobiles to mark attendance with time and location stamps. In addition, employers can enable geofencing to allow workers to mark attendance only from allowed geographical boundaries.

• Easy integration with other systems: Facial recognition attendance systems can be integrated with payroll solutions to track employee work hours and generate salary.

• Automated attendance reports: Employee attendance data is automatically fed into the system, making it easy to get information anytime and calculate attendance-based salary.

Face Recognition System: Myth Busters

• Myth #1: All Face Recognition Systems Work the Same

  No, face recognition algorithms can widely differ from each other while the aim is the same. A developer may prioritize one factor over the other or skip something completely.

  The dataset used during the testing phase will also be different. There are differences in data storage, access restrictions, privacy, and much more.

• Myth #2: Face Detection Systems are not Accurate

  In recent years, the accuracy of face recognition has improved significantly. In ideal conditions, the best face recognition tracking systems can reach a 99.97% accuracy level, according to research by the Center for Strategic and International Studies (CSIS). However, there may still be issues incorrectly identifying certain tiny subsets of data, like some identical twin people.

  If you are worried that face recognition would not work in low-light conditions, that is not the case. The system can have artificial illumination or even use a visible light image sensor to build the 3D map of the object in front of it.

• Myth #3: Face Detection Systems are Expensive

  Though the process looks expensive with high-end hardware requirements, consumer products are not as expensive now. This is because of the focus on efficiently implementing face detection and recognition without a high processing power.

• Myth #4: Hackers Can Track You with Faceprint Data

  The benefit of storing faceprint instead of actual images is that it cannot be reverse engineered to obtain the image again. A different face recognition system cannot decrypt even the faceprint since the algorithm would be different. As the image itself is not stored in the database, the process is secure.

Face Recognition with Mask: Covid-Mask Challenge

Before the coronavirus pandemic, face recognition with masks was mostly incorrect as the models were not trained to recognize faces in such instances. The struggle in identifying faces was highest with black masks.  

But now, there has been a vast improvement in accuracy, especially in one-to-one systems where just one person is to be identified. This is possible by designing algorithms that focus on the uncovered areas like eyes, eyebrows, and nose bridge. The images of masked faces are used to prepare the algorithms.  

The true Face attendance system is one such software that uses advanced AI to accurately screen visitors and employees for face masks at the organization’s entrance. In addition, it auto-captures employee’s faces and records attendance for sign-in and sign-out in a contactless manner.  

It can also identify people under low light conditions with any change of facial attributes like beard, spectacles, aging signs, etc. With Aarogya Setu integration, True works perfectly to ensure COVID-compliant entry. Companies like Bitwise, Bajaj, Titan, Fiat, HM Clause, and Bristlecone are already using it.   

In another instance, NEC, a Japan-based company working on facial recognition with masks for people with allergies before the coronavirus pandemic, now claims an accuracy rate of more than 99.9% and a verification time of less than a second.

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