What's facial recognition technology - Mitek Systems

Facial recognition technology is just one phrase that’s become increasingly homogenized in our digital age. In fact, there are some important distinctions to learn about the technology and how it's used for facial authentication and facial comparison. Read on to learn more.

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If you’re here, then it’s obvious you’re interested in researching cutting-edge tech. It’s not just a hobby – it’s a way of life.

Like most technology buffs, you’ve likely watched (or at the very least heard about) the show Black Mirror. Without getting too deep into the series, it discusses what happens when humans start to interact with and incorporate technology in their daily lives, and the ensuing pros and cons of its increased use in our digital world (see our other blog The pros and cons of biometrics).

The creator, Charlie Brooker, is a humorist and a satirist that goes to extreme lengths with the show to point out how technology envelopes our lives – a show, which ironically, is hosted on a streaming service that wants you to binge TV. But, one of his best subtle tricks with the series is in the name of the series itself.

"Any TV, any LCD, any iPhone, any iPad — something like that — if you just stare at it, it looks like a 'Black Mirror,' and there's something cold and horrifying about that, and it was such a fitting title for the show," Brooker told The Guardian in .

As we stare into our own ‘Black Mirrors’ -handheld devices, tablets, phones, and computer screens- some of them stare back using Facial Recognition Technology. This technology can authenticate and verify a user by using biometrics before authentication and allowing access. But there’s some important distinctions to make. For this next piece in our Biometric series, we’ll discuss what is facial recognition vs. facial comparison, how they are different, and how it’s used in cutting-edge technology like facial comparison.  

When the Black Mirror stares back – What is facial recognition and facial authentication?

Biometric identity verification technologies like Facial Recognition and Authentication now ubiquitous. A lot of the most popular phones in the world today have replaced a fingerprint as the de facto biometric authenticator and use a person’s face instead. What’s exciting, people are beginning to use this biometric technology (see our What are biometrics - A complete guide) in more ways than just unlocking phones: airport terminals use Facial Recognition technology to speed passengers through long security lines; sharing-economy companies use Facial Recognition technology to conduct background checks on prospective contractors; law enforcement uses Facial Recognition technology to search an image database of known criminals in order to find and compare a match.

But as Facial Recognition technology offered unprecedented convenience and spoof-proof capabilities a few months ago, its efficacy is in the news again. Recently, people find it hard to open their phones while wearing face masks in order to comply with new COVID-19 recommendations from governments. Biometric Update discussed technology reporting and testing standards with Patrick Grother from the National Institute of Standards and Technology (NIST) about their plans for future biometrics testing and Facial Recognition technology as a result of the pandemic: “What happens when you occlude the mouth region with a face mask? And is face recognition undermined by that to any great extent?” Grother asks. “That’s one example of what we’re trying to do to support informed usage of face recognition with more quantitative data.”

As facial recognition technology continues to undergo new iterations and changes as a result of changes people’s everyday lives, it’s important to note key items around phrasing that industry professionals use to describe it. Oftentimes, providers will throw out terms like facial recognition, facial authentication, and facial comparison. Though similar, each phrase refers to different, nuanced ways of using the biometrics-based technology. Conceptually, each describes a use to verify that a biometric -in this case an image of a human face- matches another image that’s stored as a template and supplied by the user. But the practices are different.

What are the differences between facial recognition, facial authentication, and facial comparison?

The thin line between facial recognition and facial authentication

Facial recognition operates using multiple images that are stored either on a personal device, or in a larger server / database. The user will be captured from a source image -in this case a picture of a person’s face- in order for the Facial Recognition system to run an analysis on other stored images and find a match. The delineating factors:

• A user may not control the Facial Recognition device
• A user may not knowingly provide a source image
• A user’s image may not be the only biometric template profile that’s stored
• A user’s own facial biometrics may not be the only profile that it gets matched against

Examples of facial recognition: a Facial Recognition system used in surveillance purposes is looking for a person with brown hair - the Facial Recognition surveillance technology will return multiple hits of people with brown hair. Those hits or matches might not include the intended user or person of interest. Security and law enforcement services will employ Facial Recognition technology to find criminals in large databases housing hundreds or thousands of biometric profiles, and are notified when there are possible matches.

How facial recognition technology is used for facial authentication: Facial Recognition technology is commonly used for security purposes like securing a physical or digital perimeter for surveillance, but it operates only returning “possible matches.” Facial authentication is actively used to admit a qualified and approved person into a secured location via facial biometric scanning. Secure a bank vault that only opens via an Iris scan? Very 007, but that’s facial authentication. Have a unlock after the qualified owner’s puts their face in front of? Secured using facial authentication.

Examples of when businesses use facial authentication: Facial images provided by a user are searched and scanned against a company’s database that contains all of its employees’ facial biometrics. A verified employee trying to access a restricted area is only permitted on a successful match with their picture that’s in the digital vault.

Facial comparison – how it’s used to verify and authenticate

Facial comparison is used in real-time, where an image of a person’s face and biometrics are readily available to compare to another, separate source of it. The source doesn’t always have to be a biometric template that’s been uploaded and stored in the cloud or physical server – some APIs and services may not store biometric templates at all. This means a user has to provide another, trusted source of their face in order to verify their identity at the moment of capture.

In order to effectively use facial comparison, there’s some important requirements:

• The user needs to be present
• A user needs to provide a trusted source picture
• The technology needs to confirm the source picture is authentic

When these are met, facial comparison will run an analysis to confirm a match. In layman’s terms and more modern practices: a user provides an identity document (like driver’s license and passport), the system validates the document isn’t a forgery, the facial comparison technology analyzes the biometrics between the user’s face and the picture on the provided document to ensure they’re the same.

How facial comparison technology is used: A common use-case for Facial Comparison is during digital account onboarding. Document verification technology, like Mitek’s Mobile Verify, is used to verify the authenticity of an applicant’s passport, ID card, or driver’s license. Once the authenticity of the ID is approved, the applicant is asked to provide a selfie. Facial comparison technology then compares the captured selfie images with the image from the verified ID to prove the user is both present and is who they say they are.

Here’s how facial comparison might be used in a bank’s digital onboarding platform:

• A person downloads a Bank’s app in order to apply for a loan
• The bank, using a digital identity verification service running facial comparison, asks the user to provide an identity document for authentication
• The user takes a picture of the Identity Document
• An image of the user’s photograph from the ID as well as other important classifiers like UV stamps, barcodes, and font are extracted from the document to determine whether or not the ID legitimate
• If the ID is approved, the user’s picture from the document becomes the trusted source image, or baseline template, for the Facial Comparison
• The software will then ask for a selfie of the user. *Note: more advanced systems use “Liveness Detection” which is like a live selfie to show a person is real
• Facial Comparison takes the trusted source image from the document and… here’s the kicker, COMPARES it with the user in the captured selfie
• If the user’s facial biometrics in the selfie and ID photograph match, the user is approved to get their loan

*Note* that more sophisticated facial comparison technologies incorporate a feature called liveness detection that walks users through a live, selfie-taking process instead of uploading any picture they want. A main positive about liveness detection is it’s nearly spoof-proof capabilities. Liveness detection walks users through a digital capture process to ensure a real person is present by having them do things like blink, turn their head, and smile.

From facilitating international travel to preventing retail theft, face recognition technology is transforming the way we live and work. In this article, we’ll explore the pros and cons of facial recognition in depth, explaining why we think the benefits outweigh its (current) drawbacks.

A quick introduction to face recognition

Facial recognition is a type of AI-powered technology that works by analyzing and identifying our unique facial features.

By identifying a human face in an image or video, face recognition software extracts unique features—like the space between your eyes or the curve of your cheekbones—and compares this data to a stored database for recognition or verification.

The facial recognition market, valued at USD 3.86 billion in , is projected to grow at a CAGR of 15.4% from to , according to Grand View Research.

Recognized for its speed, accuracy, and reliability, face recognition has found widespread adoption in security, surveillance, and access control, as well as mobile technology, where it’s already widely used for device unlocking, payment verification, sorting photos, etc.

The pros of face recognition

First, let’s look at the pros of face recognition, illustrated by real-life examples.

➥ Enhanced security and safety

Facial recognition technology is already known for high speed, accuracy, and reliability. This makes it ideal for areas where quick and accurate identification is crucial for maintaining a high level of security.

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For example, the US Customs and Border Protection (CBP) has committed to using facial recognition technology on 97% of international passengers by . The CGP’s process involves scanning travelers with a camera that matches their live image with existing photo templates from travel documents. Once matched, they can proceed to enter or exit the United States.

Another example is the Dubai International Airport. They use facial recognition cameras for passenger clearance, eliminating the need for passports or boarding passes. It can also be used in retail to identify known shoplifters, like the system used in certain British stores. When someone on the “shoplifter watchlist” enters the premises, artificial intelligence recognizes their face and immediately alerts security officers.

Image: Visage Technologies’ FaceRecognition used for border control. Read the case study here.

➥ Fraud prevention

Face recognition can be used to authenticate customers, reducing the risk of identity theft and fraud. This is especially important in banking and finance.

As an example of a significant development in the sector, HSBC introduced facial recognition banking for its corporate customers in . It allows customers to access mobile banking using a system that analyzes over 30,000 reference points to create a “depth map” of the face. This replaces the need for traditional passwords and passcodes, which can be forgotten or compromised. Also, it speeds up login times to less than a second. 

➥ Convenience and efficacy

The iPhone X was the first smartphone to introduce face recognition in , also known as Face ID. From simply unlocking the to authorizing other types of actions, it became a very convenient feature for end users, prompting other manufacturers to incorporate it by default. 

The fact that face recognition can run offline is also particularly useful for speed and efficiency since it doesn’t rely on an internet connection. For instance, our FaceRecognition has an execution time as short as 26ms. This is why the independent world-renowned NIST evaluation placed it among the fastest and lightest algorithms.

Also, the ability to use face recognition at a distance not only enhances convenience but also promotes hygiene. This offers a distinct advantage over other biometric methods that require physical contact. This becomes particularly crucial during health crises such as epidemics or pandemics. During the COVID-19 pandemic in , the contactless nature of facial recognition technology proved to be a significant asset for reducing the risk of virus transmission while maintaining security and efficiency.

➥ Personalization

Facial recognition technology can also enable personalization in various situations. For example, driver monitoring can be used to automatically adjust car settings to the preferences of a specific driver or passenger, including lighting, heating, seat position, content recommendations, and more.

In hospitality, hotels can use facial recognition to identify returning guests and personalize their experience. According to Oracle’s Hotel report, 56% of consumers said locking and unlocking rooms using biometrics and facial recognition would enhance their stay.

➥ Improved user experience

By eliminating the need to remember passwords or carry ID cards, face recognition makes everyday tasks more seamless. In customer-facing industries like retail or hospitality, this can lead to higher customer satisfaction and loyalty.

A prime example of this is Mastercard’s new payment system, which allows customers to complete payments with face recognition. This approach not only simplifies the payment process but also adds an extra layer of security, further enhancing the user experience.

The cons of face recognition

While facial recognition technology offers numerous benefits, it’s important to acknowledge and address the potential downsides. Still, there is a solution to each of these challenges, which we’ll explain below.

➥ Privacy concerns

The use of facial recognition technology inherently involves the collection, storage, and analysis of biometric data. This can raise concerns about privacy and data security. If not properly protected, private data could be vulnerable to breaches, potentially leading to misuse of personal information.

However, these concerns can be mitigated with responsible use of the technology, clear policies, and regulations in place to protect individual privacy. This includes obtaining informed consent before collecting biometric data, ensuring its secure storage and handling, and maintaining transparency about how this data is used.

➥ Difficulties in certain conditions

Facial recognition systems can occasionally encounter difficulties with variations in lighting, angles, and facial expressions. For instance, a face that is well-lit during the day may appear very different under dim lighting conditions at night. Also, most facial recognition systems are trained on frontal images of faces, but in real-world scenarios, faces are often turned to the side or tilted up or down.

One possible solution to these challenges is the implementation of multi-modal biometric systems. These systems integrate multiple biometric technologies, ensuring that the limitations of one are compensated by the strengths of others.

In addition, ongoing technology advancements are helping to improve the robustness and accuracy of facial recognition systems in every type of situation.

➥ Bias

Some facial recognition systems have faced criticism for racial and gender bias. This can occur when the algorithms used in facial recognition are trained on datasets that do not adequately represent diverse populations. 

However, ongoing advancements in technology and training methodologies are helping to mitigate these issues. By using more diverse training datasets, the algorithms can learn to recognize a wider range of facial features and skin tones, reducing the potential for bias. 

➥ Facial spoofing and impersonation

Facial recognition systems, while sophisticated, are not completely foolproof. There is a risk that they could be deceived by photos, masks, or other forms of impersonation. This is often referred to as “spoofing”.

However, these types of risks are significantly reduced by advanced features like Liveness Detection, which is included in our FaceRecognition solution. Liveness Detection can differentiate between a live person and a photo or mask. This makes it much harder for someone to gain unauthorized access.

Conclusion: face recognition has more benefits than drawbacks

In light of all these considerations, it’s clear that the pros significantly outweigh the cons when face recognition technology is used responsibly and ethically. 

The advantages are substantial and wide-ranging, offering enhanced security, fraud prevention, convenience, personalization, and improved user experience. Its high speed, accuracy, and reliability make face recognition a valuable tool in a variety of sectors and applications.

Although face recognition is faced with certain challenges, all of them can be mitigated: 

• Privacy concerns can be mitigated through responsible use of the technology, clear policies, and robust data protection measures. 
• Difficulties related to lighting, angles, and facial expressions can be addressed through the implementation of multi-modal biometric systems, and improved by ongoing technological advancements. 
• Bias can be reduced by using diverse training datasets and leveraging artificial intelligence and machine learning to improve accuracy. 
• The risk of facial spoofing and impersonation can be significantly reduced through advanced features like our Liveness Detection.

Interested in a face recognition solution? 

We’re here to help you get started.

At Visage Technologies, we have over two decades of experience in developing cutting-edge computer vision technology. This makes us well-equipped to assist you in implementing or improving your existing facial recognition solution.

Our FaceRecognition is not only powerful and flexible. It’s also one of the fastest and most lightweight solutions available on the market. It is available for all platforms and embedded systems, prioritizes privacy, and includes liveness detection to prevent spoofing attempts. If you require custom development options, we’re ready to assist with that as well.
Contact us to activate your free evaluation license and try FaceRecognition for yourself.

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