The Connection Between Biometric Technology and AI
Ever wondered how your phone gets unlocked itself just by bringing your face close to it, or by touching your finger on the sensor? ‘Face recognition’ and ‘Fingerprint scanning’ are the common words which you must have heard. But what’s actually hidden behind these? Let’s find out!
What is Biometric Technology?
The term “biometrics” is derived from the Greek words “bio” (life) and “metrics” (to measure), which literally means — “the measurement and analysis of unique physical or behavioral characteristics of life”.
Biometrics are the unique physical characteristics and biological measurements that can be used to identify humans. For example, fingerprint scanning, facial recognition, and retina scans are all forms of biometric technology. There are many other visual, behavioural, chemical types of biometrics. The technology is mainly used for access control- authentication of an individual; and for security reasons.
The question is- Are you really the same person that you are trying to prove yourself to be?
How AI Makes Biometrics Smarter?
Artificial intelligence (AI) has become a fundamental aspect of our lives, demonstrating inexplicable intelligence by machines. When employed with biometrics, it can provide multi-factor authentication making it difficult for cybercriminals to access our information. Biometric systems, with the help of sensors, convert biometric traits like fingerprints, face, iris, etc. of a person to an electrical signal. AI stores the data, and transforms the distinct individual traits into codes which are easy to understand by the system. Hence, AI and biometrics together will eventually create dynamic security models. FACIAL RECOGNITION and FINGERPRINT SCANNING are two of the most prominent biometric technologies where AI finds its application.
Facial recognition is the process of verifying the identity of a person using their face. This technology performs authentication based on the person’s facial details. Detection, capture and matching of facial details are the three major steps involved in it.
Identification puts forward the question: “Who are you?”
Authentication answers the question: “Are you really who you say you are?”
To begin with, a 2D or 3D sensor detects and captures a face which then transforms it into digital data by applying an algorithm. The captured image is compared to those images which are held in the database.
AI essentially utilizes 3D biometrics to successfully authenticate an individual’s face and learns from millions of images. AI systems can also use predictive modelling to analyze the effects of ageing on human faces which improves the technology.
With technology literally at our fingertips in today’s time, fingerprint scanning is more relevant now than it was ever before.
A fingerprint refers to an impression left by the friction ridges of a human finger. Human fingerprints are detailed, nearly unique, difficult to change, and after a certain age, remain the same over the life of an individual. This is why they are used for identification purposes.
Fingerprint scanners collect an image of a person’s fingerprint and record its features , such as the ridge lines. The collected data is matched with the existing data. The conventional fingerprint-scan systems analyze only partial fingerprint scans which can generate inaccurate results.
AI can beat standard biometrics by deceiving it using synthetic fingerprints. So, what we do is integrate this threat, and make it the sharpest arrow in our quiver. AI integrated with biometrics can increase the security and consistency by a thousand-fold.
Apart from these prominent biometrics, here are few other common technologies:
Natural language processing (NLP) is the branch of artificial intelligence that deals with analysing human voice , and converting it into a machine-readable format. Voice biometric solutions digitise words by reducing them to small segments which comprise of encoded frequencies , and produce a model “voice print” which is unique to a person.Speech recognition and AI play an integral role in NLP models which form the basis of human voice recognition systems.
Behavioural biometrics analyse the unique patterns in human activities, such as signature analysis, device usage. Such behavioural biometrics can be used for an additional level of security to fill the gap of authentication. AI plays a key role in analysing the behavioral biometrics such as , the way a person holds their phone, the way they scroll and toggle through the screen, pressure someone uses when they type, etc.
Few Biometric Software Companies
1. Deep Vision
Deep vision AI is a company excelling in facial recognition software.The users are given real-time alerts and faster response based upon the analysis of camera streams through various AI-based modules.The company owns advanced computer vision technology that can understand images and videos automatically. It then turns the visual content into real-time analytics and provides very valuable insights.
2. Sense Time
Sense time is a technology offered by SenseTime is multifunctional. The aspects of this technology include the capabilities of facial recognition, image recognition, intelligent video analytics, autonomous driving, and medical image recognition.SenseTime software includes different subparts namely, SensePortrait-S, SensePortrait-D, and SenseFace.
True face is a computer vision model that helps people understand their camera data and convert that data into actionable information. It is an on-premise computer vision solution that enhances data security and performance speeds. It can help the organizations to create a safer and smarter environment for its employees, customers, and guests using facial recognition, weapon detection, and age verification technologies.
Face first is secure, accurate, private, fast, and scalable software. This computer vision platform has been used for face recognition and automated video analytics by many organizations to prevent crime and improve customer engagement.
Cognitec’s FaceVACS Engine enables users to develop new applications for face recognition. The capabilities of this software include image quality check, secure document issuance, and access control by accurate verification.
Needless to say, biometric authentication is fostering a change around the world’s security system and is being adopted widely over conventional methods of authentication. Biometric technology along with AI is paving many ways in identity verification procedures and mitigating security risks. Hence, businesses like financial institutes, education sector, healthcare can introduce AI-based biometrics for their workplaces and customers to offer user-friendly and secure authentication protocols. AI-powered biometrics may become mainstream soon as they provide more promising solutions.