Over the years, movies have fixed a futuristic fantasy in our minds that a time will come when software would be used to recognize people by their faces. A time when our faces will be our ID cards. With advent of facial recognition technology, that time is already here.

Today, along with drones, AI and IoT, facial recognition technology is also defining our millennium. Facial recognition is a biometric technology used for authentication and examination of individuals by correlating the facial features from an image with the stored facial database. Face Recognition is one of the most popular applications of image analysis software and no more considered as a subject of science fiction. Earlier, this technology was only used for security and surveillance purposes, but it has safely transitioned to the real world in recent times. Today, companies are pitching facial recognition software as the future of everything from retail to policing. The National Institute of Standards and Technology (NIST), which regularly conducts Face Recognition Technology Evaluations (FRTE), reports that the top-performing algorithms now exhibit unparalleled accuracy. Under optimal conditions, these systems can achieve accuracy rates above 99.5%, with certain verification algorithms reaching up to 99.97%.

The Facial Recognition- “Saga”

Woody Bledsoe, Helen Chan Wolf, and Charles Bisson are known to be the pioneers of facial recognition technology. During the 1960s, they worked on recognizing human faces using a computer but only a part of their work was published and recognized since their project was funded by some intelligence agency. Later in the 1970s, Goldstein identified 21 facial measurement points. Later in 1988, Kirby & Sirovich normalized a face image using less than 100 measurement points. Finally, in 1991, first crude facial detection was done by Turk & Pentland. 

Facial Recognition – “The Last Step”

A facial recognition system is used to identify and verify a person from an image or video source. It uses biometric software’s along with AI enabled devices for mapping facial features and brings out the recognition step. A facial recognition software differentiates a face from rest of the background in the image. The software first recognizes the face then measures different facial features. The software recognizes these features as nodal points. A human face consists of 80 nodal points. After measuring these features a numerical code for the same is created and stored in the database. This is known as the faceprint.

Earlier the software relied on 2D image to identify or verify another 2D image from the database but today it uses a 3D model for the same. This 3D model is more reliable, better, effective and accurate than its 2D counterpart. Using the 3D software, the system goes through a series of steps, facial recognition forming the last one.

Face detection is the first step of process wherein face is detected from an image or a video. Once a face is detected, the system identifies its size and position. In the next step, a faceprint is generated by measuring the facial features. Finally, using the principle of object classification, the actual process of matching data features to the details of individuals already stored in database is done and facial recognition process is complete. 

Application of Facial Recognition

There are numerous applications of facial recognition. They can be segmented into blacklist and whitelist applications. Blacklist applications include the ones related to security & surveillance and identification of criminals. The all other applications such as attendance tracking, access control and others fall under the category of whitelist applications.

Array of Industries in which Facial Recognition has penetrated so far

Facial recognition is gaining traction in recent times, owing to the benefits it offers over traditional surveillance techniques, like biometrics. Facial recognition market is growing at a rapid pace and is expanding to various verticals including government, healthcare, security, retail, marketing, airport boarding’s, entertainment and many more. Automotive industry is leveraging the potential of facial recognition and implementing it in smart cars that start only upon recognizing the driver. Furthermore, dating sites are also using this technique to match people with similar attributes.

Innovation Trends Shaping Facial Recognition in 2025

Contactless Biometrics

As hygiene and user convenience become a top priority, contactless biometrics is gaining significant traction in facial recognition systems. Contactless solutions allow for the identification and verification of individuals without any physical interaction with the device, which is particularly important in public spaces and during health crises like the COVID-19 pandemic. This trend eliminates the need for touching surfaces like fingerprint scanners or card readers, reducing the risk of contamination while enhancing the user experience. The demand for frictionless access to secured spaces in industries like healthcare, finance, and transportation is driving this change.

2. Multi-Modal Biometric Authentication

While facial recognition continues to lead in biometric identification, the trend toward multi-modal biometric authentication is expected to flourish by 2025. This involves combining different biometric traits—such as facial features, fingerprints, iris patterns, voice recognition, and even gait analysis—into one cohesive authentication system. By integrating multiple modes of biometric verification, these systems offer a higher level of security and accuracy, reducing the chances of false positives and ensuring more reliable identity verification. This approach is particularly useful in high-security environments and for applications requiring robust, fail-safe authentication.

3. AI-Powered Advancements

Artificial Intelligence (AI) is at the forefront of transforming facial recognition technology. By 2025, AI algorithms will become more advanced in learning and adapting to the vast diversity in human faces. AI will help improve the precision of recognition, even in challenging environments, such as low lighting, extreme angles, or when subjects wear masks or glasses. Deep learning models will enable real-time analysis and decision-making, allowing facial recognition systems to identify individuals faster and with more accuracy. AI will also contribute to the continuous evolution of facial recognition algorithms, making them more adept at handling complex scenarios and evolving user behaviors.

4. Liveness Detection

One of the biggest concerns with facial recognition systems is the risk of spoofing, where a photo or video is used to trick the system into granting unauthorized access. Liveness detection addresses this issue by ensuring that the person being recognized is actually present and alive during the identification process. By 2025, liveness detection techniques will become more sophisticated, integrating advanced methods like 3D mapping, infrared scanning, and behavioral biometrics (such as micro-movements and blinking). These measures will make it much harder for fraudsters to deceive facial recognition systems, thereby enhancing security in critical applications, from financial transactions to border control.

5. Anti-Spoofing

As facial recognition systems become more widespread, the need for robust anti-spoofing technologies is increasing. Anti-spoofing techniques aim to prevent fraudulent attempts to bypass facial recognition systems using photos, videos, or 3D models. By 2025, facial recognition systems will incorporate more sophisticated anti-spoofing mechanisms, such as dynamic texture analysis, eye movement tracking, and depth sensing. These technologies will be designed to detect signs of artificial manipulation, such as mismatched lighting, unrealistic facial expressions, or synthetic images, significantly reducing the vulnerability of systems to spoofing attacks. This will be especially important in sectors like banking, government, and security.

According to TechSci Research report “Global Facial Recognition Market By Component (Software & Services), By Software Type (2D, 3D & Thermal Face Recognition), By End Use Sector (Government & Transportation, Military & Defence, etc), By Region, Competition Forecast & Opportunities, 2023”, the global facial recognition market stood at around $ 2.9 billion in 2017 and is expected to grow at a CAGR of 13% by 2023, on account of growing criminal activities and increasing need for enhanced monitoring and surveillance. Moreover, rising awareness about the benefits of facial recognition and growing implementation by the commercial sector is further expected to push the demand for facial recognition technology in the coming years. Government, transportation and military & defence are the largest contributors to the global facial recognition market as these end use sectors are adopting facial recognition for real time identification of criminals and to provide more secure environment. Additionally, huge National ID Programs like ‘Aadhaar’ in India are also boosting the face recognition market as they involve recording the facial biometrics of individuals. 

Key players in the Facial Recognition industry

Aware, NEC Corporation, Ayonix Corp., Cognitec Systems, KeyLemon, nViso, Herta Security, Techno Brain, Neurotechnology, Daon, Animetrics, 3M Company, IDEMIA, and Gemalto are some of the leading players of the facial recognition industry. Companies operating in the market are using organic strategies such as product launches, mergers and collaborations to boost their share.  For example, in 2015, Cognitec Systems launched and incorporated a superior version of the face recognition algorithm B9 in FaceVACS-DB Scan, one of its leading facial recognition products. Also, Gemalto in 2017, supplied new automated control gates for the PARAFE system (Automated Fast Track Crossing at External Borders) at Roissy Charles de Gaulle airport in Paris to facilitate transfer from fingerprint recognition to facial recognition.

Global Facial Recognition Scenario

Governments around the globe are investing significant resources in facial recognition technology, among which, the United States and China are at the forefront of the facial recognition market. The US government is planning to reshape its airport security through facial recognition system for registration and identification of visitors. There are many states in the US that allow law enforcement to run searches against their databases of driver’s license and ID photos. The FBI also has access to driver’s license photos of many states. This technique can also be employed in police checks, although its use is rigorously controlled in Europe. In 2016, the "man in the hat" responsible for the Brussels terror attacks was identified by FBIs facial recognition software.

Several projects in China pertaining to facial intelligence are already in action, while most of them in other countries are only at the planning stage. The most pervasive facial recognition surveillance exists in China. Its facial recognition dragnet can locate a BBC reporter wandering across a city of 3.5 million people in a mere seven minutes. Best feature of this technology is that the police can use both cameras and smart glasses to catch the criminals. This approach is also helpful in tracking jaywalking cases.  When people jaywalk, their photo appears on a LED billboard and then they are notified and fined.

At a KFC branch, in China payments are made using facial recognition. There is a screen equipped with the technology where customers can make payments just by smiling. The system then investigates its database and asks for a phone number for an added security check. Some banks are even allowing customers to use their faces instead of bank cards.

Additionally, facial recognition can also find application as Humanoid robots. Facial recognition is being used for identification of rare genetic diseases, also the symptoms for different disorders can be recognized and prescription is suggested accordingly.

Japan also has some perspectives and some already working projects. For instance, there is an automobile company Subaru, that has integrated facial recognition cameras into its new brand of SUVs, the Forrester. The new vehicles can predict when a driver is tired or falling asleep and can act if an accident could happen. Facial Recognition will be used in Tokyo Olympics 2020 at the entrance for security purposes instead of relying on ID cards for making an entry. AI-powered cameras are also being used for catching shoplifters, verifying bank employees and others.

UAE also has big ambitions when it comes to Facial Recognition. A virtual aquarium with 80 facial recognition cameras is fitted at the Dubai airport which examines people when they pass through the aquarium. Police cars are also being fitted with facial recognition cameras. At present this is in the testing phase.

UK has also adopted facial recognition technology and is using it in schools as attendance tracking system. The system is being used to maintain discipline in the schools and is also helpful in detecting any kind of threats to the school.

Scope of Facial Recognition Technology in India

The world is using facial recognition technology and enjoying its benefits. Why should India be left out? There is a huge scope of this technology in India and it can help improve the country in various aspects. The technology and its applications can be applied across different segments in the country.

• Preventing the frauds at ATMs in India. A database of all customers with ATM cards in India can be created and facial recognition systems can be installed. So, whenever user will enter in ATM his photograph will be taken to permit the access after it is being matched with stored photo from the database.
• Reporting duplicate voters in India.
• Passport and visa verification can also be done using this technology.
• Also, driving license verification can be done using the same approach.
• In defence ministry, airports, and all other important places the technology can be used to ensure better surveillance and security.
• It can also be used during examinations such as Civil Services Exam, SSC, IIT, MBBS, and others to identify the candidates. Facial recognition technology is being utilized in educational institutions for authentication to access academic records.
• This system can be deployed for verification and attendance tracking at various government offices and corporates.
• For access control verification and identification of authentic users it can also be installed in bank lockers and vaults.
• For identification of criminals the system can be used by police force also. For instance, facial recognition technology is being deployed in India for multiple purposes, such as identifying criminals (through Trinetra in Uttar Pradesh) and locating missing individuals (via Darpan in Telangana).

       Some Concerns That Need To Be Addressed

What the Future Holds?

The future of facial recognition technology is bright. Forecasters opine that this technology is expected to grow at a formidable rate and will generate huge revenues in the coming years. Security and surveillances are the major segments which will be deeply influenced. Other areas that are now welcoming it with open arms are private industries, public buildings, and schools. It is estimated that it will also be adopted by retailers and banking systems in coming years to keep fraud in debit/credit card purchases and payment especially the ones that are online. This technology would fill in the loopholes of largely prevalent inadequate password system. In the long run, robots using facial recognition technology may also come to foray. They can be helpful in completing the tasks that are impractical or difficult for human beings to complete.