Face Recognition [What is it and how does it work?]
To prevent the use of digital identities for criminal purposes, facial recognition has become a widespread tool in many countries. The demand for facial recognition software is increasing every year, with the market expecting to grow by $7.7 billion by 2022, and a large portion of its current use is to identify and authenticate users.
What is Face Recognition?
Many people are becoming increasingly familiar with facial recognition technology due to unlocking features in new phones requiring face ID. In this use case, facial recognition is used to determine that the individual is the owner of the device and authorize access to the phone.
Facial recognition is a technology that can match a human face from a digital image or video, against a database of stored faces. Facial recognition generally uses biometrics to help identify facial features. This type of identification is helpful for various commercial and law enforcement applications. When it comes to digital authentication, facial recognition falls under the category of biometrics.
Facial Biometrics: How It Works
Biometrics are biological measurements or physical features that are used to identify individuals. Some common forms of biometrics include fingerprint mapping, retina scans, and facial biometrics. Facial biometrics works through:
- Face Detection: The camera detects and locates a face individually or present in a crowd
- Face Analysis: The image of the face is captured and analyzed. Most variants of facial biometric technology tend to rely on 2D images rather than 3D images. The software finds the geometry of an individual’s face, like the distance between their eyes, distance from forehead to chin, etc. Facial landmarks are identified to make it easier to distinguish a face in a database and a real live person.
- Converting the Image: The captured face image (analog information) is transformed into a set of digital information (data) depending on an individual’s facial features. The numerical code is known as a faceprint. Each individual has a unique faceprint
- Finding the match: A unique faceprint is compared to a database of other known faceprints. A correct match has been made if the unique faceprint is matched to a known one in the database.
Compared to other types of biometric recognition, facial recognition is considered the most natural form of matching, because that is how humans actually differentiate one person from another: by comparing facial features.
The Purpose of Face Recognition
The main objective of facial recognition is to identify individuals, whether individually or collectively. The number of false positives can vary, depending on the technology used for facial recognition. The best face identification algorithm has an error rate of 0.08%. Facial recognition systems that operate with liveness detection, have higher rates of accuracy.
There are various benefits of facial recognition, depending on the industry and application. It can be a convenient, safe, and hassle-free method to identify a person at a distance without any physical contact. Facial recognition, when used correctly, has led to increased security functions, decreased instances of crime, faster processing, and greater convenience for the public. There are however concerns about the introduction of bias into systems that rely on facial recognition. Most recently Facebook announced that it is stopping the use of facial recognition to recognize people on its platform.
Applications of Face Authentication Technology
There are various applications of face authentication technology for law enforcement and other commercial ventures. Law enforcement agencies in the U.S and globally are beginning to rely on facial recognition to find suspected criminals by adding mugshots and other photos to their database. Once added to the database, the facial images are scanned whenever the police department carries out a criminal search.
Mobile face recognition has also enabled officers to use smartphones and other portable smart devices to take a photo of a driver or pedestrians and compare it to face recognition databases to identify individuals accurately.
In airports, border control security now uses facial recognition in conjunction with biometric passports. It enables commuters to skip the regular long lines in favor of a quicker automated gate that uses facial recognition to match the traveler with their passport image.
Online banking has also received a substantial boost thanks to biometric functions, specifically facial authentication. Customers can opt to authorize transactions simply by looking at their phones or laptops instead of accepting and manually entering a one-time password (OTP) on their devices.
Facial recognition is also used for entertainment purposes. Snapchat, Instagram and other social media platforms recognize faces and make fun and creative filters for people to enjoy. It has led to widespread usage of specially created filters that detect your facial features and adapt accordingly.
Facial Recognition Technology and Mobile Security
The integration of facial recognition systems with mobile security has been advantageous to consumers and mobile companies alike. Many people store critical information on their phones, and criminals are increasingly targeting mobile users to steal and hack their phones to gain this information.
With the introduction of facial recognition systems, many phone manufacturers are making face IDs a method of identification for users to access their phones. The intention is to protect personal data and ensure that sensitive data is inaccessible to those with malicious intent.
Apple is considered a pioneer in facial recognition for smartphones. It enabled its users to unlock their phones using Face ID and access specific locked apps, and even pay for various services just by scanning their face with the phone front camera.
Increasingly there are concerns, and research studies showing that face recognition software can be fooled by deep fake technology making its use for authentication increasingly vulnerable to sophisticated cybercriminals.