Biometric facial recognition technology utilises facial feature analysis to identify and verify individuals’ identities accurately.
It allows for identifying individuals in photos, videos, and real-time situations. This method is classified under biometric security alongside fingerprint, voice and iris recognition.
While facial recognition technology is commonly utilised in law enforcement and security applications, there is an increasing interest in its application in various other fields.
What is the Mechanism Behind Facial Recognition Technology?
The familiarity of facial recognition technology is widespread, with applications like FaceID on iPhones being recognized by many individuals.
In these instances, facial recognition technology doesn’t rely on a vast database of images to ascertain someone’s identity. Instead, it focuses on recognizing the owner of the device, thereby restricting access to unauthorised individuals.
In the context of unlocking phones, facial recognition operates by comparing the user’s face, captured by dedicated cameras, with images stored on a watch list.
These watch lists can include images of individuals, irrespective of their suspected involvement in any illicit activities. Moreover, the source of these images can be diverse, including social media accounts.
While the specific functioning of facial recognition systems may vary, they typically follow a similar pattern.
Step 1: Face Detection
The camera can identify and capture face images, whether it’s an individual alone or within a crowd. The images can depict individuals facing straight ahead or in a profile view.
Step 2: Face Analysis
During this step, the facial image is effortlessly captured and analysed. Facial recognition technology frequently relies on 2D images instead of 3D images, enabling effortless comparisons between 2D pictures and publicly available photos or those stored in a database.
This is due to the software analysing facial geometry, considering factors such as the eye distance, depth of eye sockets, cheekbone shape, and forehead-to-chin measurement. The objective is to identify the facial landmarks that differentiate an individual’s face.
Step 3: Transform the Image into Data
Capturing a face converts analogue data into a digital dataset based on the individual’s facial features.
This numerical code, commonly called a faceprint, represents the mathematical representation of the user’s facial analysis. Each person has their own distinctive faceprint, just like fingerprints.
Step 4: Find a Match
During this stage, the user’s faceprint is matched against a database of recognized faces. For instance, the FBI has access to a comprehensive collection of approximately 650 million photos from various state databases.
Social media platforms like Facebook also contribute to facial recognition databases, where any photo tagged with an individual’s name becomes part of their repository. The user’s faceprint is compared to the images in the facial recognition database to make a determination.
Facial recognition is widely regarded as one of the most intuitive biometric measurements, and it is estimated that over half of the global population interacts with facial recognition technology on a daily basis.
Face Recognition Advantages
Biometric facial recognition provides more benefits besides unlocking smartphones:
Basically, facial recognition helps at two levels. On a personal level, it can be used as a security tool for locking personal devices and for personal surveillance cameras. On a governmental level, it helps recognise terrorists or other scammers.
Facial recognition technology plays a vital role in tracking down and identifying individuals involved in theft, burglary, and trespassing incidents.
The mere awareness of the presence of a face recognition system can act as a deterrent, particularly for petty crimes. Beyond its application in physical security, there are also cybersecurity benefits associated with facial recognition.
Companies can leverage machine learning facial recognition as an alternative to traditional passwords for accessing computer systems.
In theory, this technology is more secure since there is no tangible element to steal or alter, as is the case with passwords. This aspect makes facial recognition an attractive option for enhancing cybersecurity measures.
Removing Bias from Stop and Search
Facial recognition technology improves the process by addressing public concerns regarding inappropriate stops and searches, which have been a source of controversy involving law enforcement.
It aids in identifying suspects within crowds through automated means, replacing traditional methods. Consequently, facial recognition helps reduce the potential for bias and decreases unnecessary stops and searches conducted on law-abiding individuals.
With the advancement of technology, customers can make payments in stores by using their facial recognition instead of cash or credit cards. This innovative approach helps save significant time by reducing the need for lengthy checkout lines.
A noteworthy advantage of facial recognition is that it does not require physical contact like fingerprinting or other security measures, making it particularly valuable in a post-COVID world.
Facial recognition provides a rapid, automated, and effortless verification experience, ensuring a seamless transaction process.
When considering the notable benefits of biometric facial recognition technology, it becomes imperative to carefully examine and address concerns related to data security, privacy, and the potential for misuse.
Striking a harmonious equilibrium among security, privacy, and convenience is crucial for facial recognition technology’s ethical and responsible deployment.