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Plant Security
Published in Frank R. Spellman, Fundamentals of Public Utilities Management, 2020
Hand and finger geometry recognition is the process of identifying an individual through the unique “geometry” (shape, thickness, length, width, etc.) of that individual’s hand or fingers. Hand geometry recognition has been employed since the early 1980s and is among the most widely used biometric technologies for controlling access to important assets. It is easy to install and use, and is appropriate for use in any location requiring the use of two-finger highly accurate, non-intrusive biometric security. For example, it is currently used in numerous workplaces, day care facilities, hospitals, universities, airports, and power plants.
Upgrading Security
Published in Frank R. Spellman, The Drinking Water Handbook, 2017
Hand and finger geometry recognition is the process of identifying an individual through the unique geometry (e.g., shape, thickness, length, width) of that individual’s hand or fingers. Hand geometry recognition has been employed since the early 1980s and is a widely used biometric technologies for controlling access to important assets. It is simple to install and use and is appropriate for any location requiring highly accurate biometric security; for example, it is currently used in numerous workplaces, daycare facilities, hospitals, universities, airports, and power plants.
Acquisition and Computation for Data in Biometric System
Published in Karm Veer Arya, Robin Singh Bhadoria, The Biometric Computing, 2019
Human hand biometrics is an ensemble of techniques leading to the establishment of a person’s identity based upon hand geometry and hand silhouette. Human hands are considerably capable of uniquely identifying a person by extracting the palm surface, length and width of fingers, etc. Hand geometry biometric systems deploy a camera or a scanner as a sensor for capturing hand images for further processing. This image information is further matched against the sample hand information in a pre-stored database for human identification and verification. Hand geometry biometric systems are not sufficiently accurate for a large population coverage where security issues are of utmost importance, but still these systems are in existence from many decades in average sized institutions for attendance purposes, person validation, etc. because of the following advantages offered by them to users: Low-resolution images are used to extract hand information resulting in the efficient storage of hand templates in database. Many commercial systems use a 9 byte template to store hand information.Sensors deployed are relatively inexpensive and provide a user-friendly environment for data acquisition.It is commonly acceptable to public as it is free from criminal connotation.Fingerprints and palm prints can easily be used in addition to hand geometry biometrics for more reliable human identification.
An Iris Recognition System Based on Analysis of Textural Edgeness Descriptors
Published in IETE Technical Review, 2018
Saiyed Umer, Bibhas Chandra Dhara, Bhabatosh Chanda
A biometric system recognizes each individual based on his/her physiological or behavioural characteristics (traits) such as gesture, fingerprint, voice-print, palm-print, handwritten signature, hand geometry, facial features, iris and gait which establish more reliability to distinguish a genuine person from an impostor. A human iris is an annular region between pupil (mostly black portion) and sclera (white portion) regions. According to [1], among the various biometric characteristics, iris has more extraordinary regular patterns which is rich in texture information. It is also evident that texture information of iris pattern is unique to each individual even between identical twins and also between the left eyes and right eyes of the same person. Moreover, among the various traits, iris is more stable and safe from spoof attacks for person identification [2]. So, in this work, we consider iris as a biometric trait and develop the proposed biometric recognition system.
Face, Fingerprint, and Signature based Multimodal Biometric System using Score Level and Decision Level Fusion Approaches
Published in IETE Journal of Research, 2023
Majharoddin Kazi, Karbhari Kale, Raddam Sami Mehsen, Arjun Mane, Vikas Humbe, Yogesh Rode, Siddharth Dabhade, Nagsen Bansod, Arshad Razvi, Prapti Deshmukh
Usually, vendors of biometric devices have suggestions for setting threshold values according to the security level you are trying to achieve. The security level may be labeled as low, medium, and high. Each security level has a threshold value associated with it as well. System performance can be improved by providing separate threshold values for each user of the system. In [12], it is shown that by providing separate threshold values for each user of the system, which consists of a combination of fingerprint, face, and hand geometry, the genuine accept rate is above 96%.
Attack Analysis of Face Recognition Authentication Systems Using Fast Gradient Sign Method
Published in Applied Artificial Intelligence, 2021
Arbena Musa, Kamer Vishi, Blerim Rexha
A biometric system recognizes a person by determining authentication by using different features of his body such as fingerprints, face, iris, retina scanning, signature, hand geometry, voice, etc. These features can be divided based on the level of security, user acceptance, cost, performance, etc. Biometrics is a growing technology, which has been widely used in forensics, access and physical security (Gill et al. 2019).