Artificial Intelligence (AI) technology is becoming part of our everyday life and its applications can be seen in areas such as bank fraud detection, retail purchase predictions and online customer support interactions. AI has also proved useful in detecting and stopping malware threats and cyber attacks. An emerging area of AI is Facial Recognition technology – the ability to identify or verify a person from a digital image or video source. Several methods are being used in which facial recognition systems work, but in general, they work by comparing selected facial features from a given image with faces within a database.
Iris recognition is one of the most popular types of biometric technology because of its narrow margin of error and fast speed. It is an automated method of biometric identification and verification that uses mathematical pattern-recognition techniques on images of a person’s eyes. The iris offers complex, unique and stable patterns and can be observed from some distance. This technology utilizes pattern recognition methods based on distortion-free and high-resolution images of the iris, and then stores the data for future faultless identification and verification.
Finger Vein Identification
The Finger-Vein biometric system is difficult to fool because of the individuality of the human fingerprint. This approach incorporates a Deep Learning algorithm using Convolutional Neural Networks (CNN) to identify unique patterns. Machines are trained in a way that captures infrared light which passes through human skin to verify unique individual vein patterns. This approach provides a highly secure and reliable identification method.
New methodologies and improved technologies in the field of biometrics have made this technology an important tool for systems that require identification or protection procedures. The far-reaching advantages of biometrics – including increased safety, ease-of-use and reduced man-hours – justify its higher application costs.
Biometrics identification and recognition solutions can be split into two main categories: Physical biometrics and Behavioral biometrics. Behavioral and physiological characteristics are distinctive properties of human beings which provide basic measurements for biometrics identification.
Physical biometrics is any physiological feature on the human body that can be used as recognition or identification. These biometrics technologies are based on direct measurements of human body parts and incorporate the ability to do a facial scan, hand scan, finger scan, iris scan, or retina scan. These are static ways to measure points obtained from a fixed image.
Behavioral biometrics, also known as ‘Gait Recognition,’ use human patterns for identification. This approach depends on measurements of information derived from an action such as data from a voice scan or signature scan. Behavioral biometrics is governed by a dynamic approach – driven by Machine Learning and Deep Learning – which involves the processing of large data sets. Thousands of behavioral patterns can be utilized to continuously authenticate users by employing primary sensing devices including gyroscopes and accelerometers. A person’s swipe speed, fingerprint area, tap duration, device acceleration and session duration are among some of the behavioral parameters that can be profiled and captured. Artificial Intelligence tools are becoming better at understanding human interaction and Behavioral biometrics is a prime example of this new approach to technology designed to meet human needs.
At accentedge, our Biometrics solutions not only offer stronger and more secure authentication, but are configured to meet our client’s individual requirements – allowing the ability to personalize and integrate biometrics identity validation into existing security infrastructures while providing the best available technology solutions.