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An authoritative survey of intelligent fingerprint-recognition concepts, technology, and systems is given. Editors and contributors are the leading researchers and applied R&D developers of this personal identification (biometric security) topic and technology. Biometrics and pattern recognition researchers and professionals will find the book an indispensable resource for current knowledge and technology in the field.
A major new professional reference work on fingerprint security systems and technology from leading international researchers in the field. Handbook provides authoritative and comprehensive coverage of all major topics, concepts, and methods for fingerprint security systems. This unique reference work is an absolutely essential resource for all biometric security professionals, researchers, and systems administrators.
Automatic person authentication, the identification and verification of an individual as such, has increasingly been acknowledged as a significant aspect of various security applications. Various recognition and identification systems have been based on biometrics utilizing biometric features such as fingerprint, face, retina scans, iris patterns, hand geometry, DNA traces, gait, and others. This book originates from an international summer school on biometrics, held in Alghero, Italy, in June 2003. The seven revised tutorial lectures by leading researchers introduce the reader to biometrics-based person authentication, fingerprint recognition, gait recognition, various aspects of face recognition and face detection, topologies for biometric recognition, and hand detection. Also included are the four best selected student papers, all dealing with face recognition.
This book describes a range of new biometric technologies, such as high-resolution fingerprint, finger-knuckle-print, multi-spectral backhand, 3D fingerprint, tongueprint, 3D ear, and multi-spectral iris technologies. Further, it introduces readers to efficient feature extraction, matching and fusion algorithms, in addition to developing potential systems of its own. These advanced biometric technologies and methods are divided as follows: 1. High-Resolution Fingerprint Recognition; 2. Finger-Knuckle-Print Verification; 3. Other Hand-Based Biometrics; and 4. New Head-Based Biometrics. Traditional biometric technologies, such as fingerprint, face, iris, and palmprint, have been extensively studied and addressed in many research books. However, all of these technologies have their own advantages and disadvantages, and there is no single type of biometric technology that can be used for all applications. Many new biometric technologies have been developed in recent years, especia lly in response to new applications. The contributions gathered here focus on how to develop a new biometric technology based on the requirements of essential applications, and how to design efficient algorithms that yield better performance.
Biometric Systems provides practitioners with an overview of the principles and methods needed to build reliable biometric systems. It covers three main topics: key biometric technologies, design and management issues, and the performance evaluation of biometric systems for personal verification/identification. The four most widely used technologies are focused on - speech, fingerprint, iris and face recognition. Key features include: in-depth coverage of the technical and practical obstacles which are often neglected by application developers and system integrators and which result in shortfalls between expected and actual performance; and protocols and benchmarks which will allow developers to compare performance and track system improvements.
Fingerprints are among the most widely used biometric modalities and have been successfully applied in various scenarios. For example, in forensics, fingerprints serve as important legal evidence; and in civilian applications, fingerprints are used for access and attendance control as well as other identity services. Thanks to advances in three-dimensional (3D) and high-resolution imaging technology, it is now feasible to capture 3D or high-resolution fingerprints to provide extra information and go beyond the traditional features such as global ridge patterns and local ridge singularities used in conventional fingerprint recognition tasks. This book presents the state of the art in the acquisition and analysis of 3D and high-resolution fingerprints. Based on the authors’ research, this book focuses on advanced fingerprint recognition using 3D fingerprint features (i.e., finger shape, level 0 features) or high-resolution fingerprint features (i.e., ridge detail, level 3 features). It is a valuable resource for researchers, professionals and graduate students working in the field of computer vision, pattern recognition, security/biometrics practice, as well as interdisciplinary researchers.
The book highlights recent developments in human biometrics, covering a wide range of methods based on biological signals, image processing, and measurements of human characteristics such as fingerprints and iris or medical characteristics. Human Biometrics is becoming increasingly crucial in forensics security and medicine. They provide a solid basis for identifying individuals based on unique physical characteristics or diseases based on characteristic biomedical measurements. As such, the book offers an essential reference guide about biometry methods for students, engineers, designers, and technicians.
This book constitutes the refereed proceedings of the First International Conference on Advanced Machine Learning Technologies and Applications, AMLTA 2012, held in Cairo, Egypt, in December 2012. The 58 full papers presented were carefully reviewed and selected from 99 intial submissions. The papers are organized in topical sections on rough sets and applications, machine learning in pattern recognition and image processing, machine learning in multimedia computing, bioinformatics and cheminformatics, data classification and clustering, cloud computing and recommender systems.
This book is the outcome of a series of discussions at the Philips Symposium on Intelligent Algorithms, which was held in Eindhoven on December 2002. It contains many exciting and practical examples from this newly developing research field, which can be positioned at the intersection of computer science, discrete mathematics, and artificial intelligence. The examples include machine learning, content management, vision, speech, content augmentation, profiling, music retrieval, feature extraction, audio and video fingerprinting, resource management, multimedia servers, network scheduling, and IC design.