Biometrics in a Data Driven World: Trends, Technologies, and by Sinjini Mitra, Mikhail Gofman

By Sinjini Mitra, Mikhail Gofman

Biometrics in a knowledge pushed international: traits, applied sciences, and Challenges goals to notify readers concerning the sleek functions of biometrics within the context of a data-driven society, to familiarize them with the wealthy heritage of biometrics, and to supply them with a glimpse into the way forward for biometrics.

The first element of the e-book discusses the basics of biometrics and gives an summary of universal biometric modalities, particularly face, fingerprints, iris, and voice. It additionally discusses the heritage of the sphere, and offers an summary of rising tendencies and possibilities. the second one portion of the booklet introduces readers to a variety of biometric purposes.

The subsequent a part of the e-book is devoted to the dialogue of case stories of biometric modalities at present used on cellular functions. As smartphones and pill desktops are swiftly turning into the dominant buyer laptop systems, biometrics-based authentication is rising as an essential component of defending cellular units opposed to unauthorized entry, whereas allowing new and hugely well known functions, corresponding to safe on-line fee authorization.

The booklet concludes with a dialogue of destiny tendencies and possibilities within the box of biometrics, in order to pave the best way for advancing learn within the region of biometrics, and for the deployment of biometric applied sciences in real-world applications.

The ebook is designed for people drawn to exploring the modern purposes of biometrics, from scholars to researchers and practitioners operating during this box. either undergraduate and graduate scholars enrolled in college-level safety classes also will locate this ebook to be a particularly valuable companion.

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Extra info for Biometrics in a Data Driven World: Trends, Technologies, and Challenges

Sample text

Face recognition can occur from both still and video images, and from both two-dimensional (2D) and threedimensional (3D) images. The problem of automatic face recognition involves three key steps/subtasks: (1) detection and normalization of faces, (2) feature extraction, and (3) identification and/or verification. For example, face detection and feature extraction can be achieved simultaneously using facial features like eyes, nose, etc. Hjelmas and Low [6] provide a highlighted summary of research on face detection and feature extraction methods.

Nevertheless, a few products, which claim to have the capability of identifying individual at distance of up to 10 m (“Standoff Iris” or “Iris at a Distance” [82] as well as SRI International’s “Iris on the Move” [83] for persons walking at speeds up to 1 m/s), have been already developed by several biometric research institutions and vendors. In association with illumination, other problems may also greatly impact the ability of the camera to capture a quality image, such as the existence of reflective surfaces under the range of the camera and any unusual lighting that may exist.

However, with huge advances in technology and increased threats of global terrorism and other dangers, new forms of biometrics gradually emerged to upgrade and improve security and identification methods. By 1974, the first commercial hand geometry recognition system became available, which was arguably the first commercially available biometric device after the early deployments of fingerprinting in the late 1960s [48]. The readers must capture both the top surface of the hand, and a side image using an angled mirror.

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