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Biometrics deals with recognition of individuals based on their physiological or behavioral characteristics. The human ear is a new feature in biometrics that has several merits over the more common face, fingerprint and iris biometrics. Unlike the fingerprint and iris, it can be easily captured from a distance without a fully cooperative subject, although sometimes it may be hidden with hair, scarf and jewellery. Also, unlike a face, the ear is a relatively stable structure that does not change much with the age and facial expressions. Human Ear Recognition by Computer is the first book on the automatic recognition of human ears. It presents an entire range of computational algorithms for recognition of humans by their ears. These algorithms have been tested and validated on the largest databases that are available today. Specific algorithms addressed include: • Ear helix/anti-helix based representation • Global-to-local registration • Ear recognition using helix/anti-helix representation • Ear recognition using a new local surface patch representation • Efficient ear indexing and recognition • Performance prediction for 3D ear recognition • Generality and applications in computer vision and pattern recognition This state-of-the-art research reference explores all aspects of 3D ear recognition, including representation, detection, recognition, indexing and performance prediction. It has been written for a professional audience of both researchers and practitioners within industry, and is also ideal as an informative text for graduate students in computer science and engineering. Professor Bir Bhanu has been director of the Visualization and Intelligent Systems Laboratory (at the University of California at Riverside) since 1991 and serves as the founding Director for the Center for Research in Intelligent Systems. He also has considerable experience working within industry and is the successful author of several books. He is a Fellow of IEEE, AAAS, IAPR, SPIE and was a Senior Fellow at Honeywell Inc. Dr. Hui Chen works alongside Professor Bhanu and has worked for Siemens Medical solutions and the Chinese Academy of Sciences.

Computer Science. --- Computer Imaging, Vision, Pattern Recognition and Graphics. --- Biometrics. --- Image Processing and Computer Vision. --- Pattern Recognition. --- Computer Graphics. --- The Computing Profession. --- Computer science. --- Computer vision. --- Computer graphics. --- Optical pattern recognition. --- Computer industry. --- Informatique --- Vision par ordinateur --- Infographie --- Reconnaissance optique des formes (Informatique) --- Industrie --- Biometric identification. --- Ear, External -- Identification -- Data processing. --- Pattern recognition systems. --- Three-dimensional imaging. --- Pattern recognition systems --- Biometric identification --- Three-dimensional imaging --- Ear, External --- Technology - General --- Electrical Engineering --- Applied Physics --- Engineering & Applied Sciences --- Electrical & Computer Engineering --- Data processing --- Identification --- Data processing. --- External ear --- 3-D imaging --- 3D imaging --- Three-dimensional imaging systems --- Three-dimensional imaging techniques --- Three-dimensional visualization --- Visualization, Three-dimensional --- Biometric person authentication --- Biometrics (Identification) --- Pattern classification systems --- Pattern recognition computers --- Image processing. --- Pattern recognition. --- Biometrics (Biology). --- Computers. --- Automatic computers --- Automatic data processors --- Computer hardware --- Computing machines (Computers) --- Electronic brains --- Electronic calculating-machines --- Electronic computers --- Hardware, Computer --- Computer systems --- Cybernetics --- Machine theory --- Calculators --- Cyberspace --- Biological statistics --- Biology --- Biometrics (Biology) --- Biostatistics --- Biomathematics --- Statistics --- Design perception --- Pattern recognition --- Form perception --- Perception --- Figure-ground perception --- Pictorial data processing --- Picture processing --- Processing, Image --- Imaging systems --- Optical data processing --- Automatic drafting --- Graphic data processing --- Graphics, Computer --- Computer art --- Graphic arts --- Electronic data processing --- Engineering graphics --- Image processing --- Informatics --- Science --- Statistical methods --- Digital techniques --- Anthropometry --- Pattern perception --- Computer vision --- Machine vision --- Vision, Computer --- Artificial intelligence --- Perceptrons --- Visual discrimination --- Electronic industries --- Optical data processing. --- Optical computing --- Visual data processing --- Bionics --- Integrated optics --- Photonics --- Computers --- Optical equipment --- Pattern perception. --- Biometry.

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The advances of live cell video imaging and high-throughput technologies for functional and chemical genomics provide unprecedented opportunities to understand how biological processes work in subcellular and multicellular systems. The interdisciplinary research field of Video Bioinformatics is defined by Bir Bhanu as the automated processing, analysis, understanding, data mining, visualization, query-based retrieval/storage of biological spatiotemporal events/data and knowledge extracted from dynamic images and microscopic videos. Video bioinformatics attempts to provide a deeper understanding of continuous and dynamic life processes. Genome sequences alone lack spatial and temporal information, and video imaging of specific molecules and their spatiotemporal interactions, using a range of imaging methods, are essential to understand how genomes create cells, how cells constitute organisms, and how errant cells cause disease. The book examines interdisciplinary research issues and challenges with examples that deal with organismal dynamics, intercellular and tissue dynamics, intracellular dynamics, protein movement, cell signaling and software and databases for video bioinformatics. Topics and Features · Covers a set of biological problems, their significance, live-imaging experiments, theory and computational methods, quantifiable experimental results and discussion of results. · Provides automated methods for analyzing mild traumatic brain injury over time, identifying injury dynamics after neonatal hypoxia-ischemia and visualizing cortical tissue changes during seizure activity as examples of organismal dynamics · Describes techniques for quantifying the dynamics of human embryonic stem cells with examples of cell detection/segmentation, spreading and other dynamic behaviors which are important for characterizing stem cell health · Examines and quantifies dynamic processes in plant and fungal systems such as cell trafficking, growth of pollen tubes in model systems such as Neurospora Crassa and Arabidopsis · Discusses the dynamics of intracellular molecules for DNA repair and the regulation of cofilin transport using video analysis · Discusses software, system and database aspects of video bioinformatics by providing examples of 5D cell tracking by FARSIGHT open source toolkit, a survey on available databases and software, biological processes for non-verbal communications and identification and retrieval of moth images This unique text will be of great interest to researchers and graduate students of Electrical Engineering, Computer Science, Bioengineering, Cell Biology, Toxicology, Genetics, Genomics, Bioinformatics, Computer Vision and Pattern Recognition, Medical Image Analysis, and Cell Molecular and Developmental Biology. The large number of example applications will also appeal to application scientists and engineers. Dr. Bir Bhanu is Distinguished Professor of Electrical & Computer Engineering, Interim Chair of the Department of Bioengineering, Cooperative Professor of Computer Science & Engineering, and Mechanical Engineering and the Director of the Center for Research in Intelligent Systems, at the University of California, Riverside, California, USA. Dr. Prue Talbot is Professor of Cell Biology & Neuroscience and Director of the Stem Cell Center and Core at the University of California Riverside, California, USA.

Biology - General --- Biology --- Health & Biological Sciences --- Image processing --- Digital techniques. --- Digital techniques --- Digital image processing --- Computer science. --- Data mining. --- Information storage and retrieval. --- Image processing. --- Bioinformatics. --- Computational biology. --- Computer Science. --- Computational Biology/Bioinformatics. --- Image Processing and Computer Vision. --- Data Mining and Knowledge Discovery. --- Information Storage and Retrieval. --- Computer Appl. in Life Sciences. --- Digital electronics --- Computer vision. --- Information storage and retrieva. --- Data processing. --- Algorithmic knowledge discovery --- Factual data analysis --- KDD (Information retrieval) --- Knowledge discovery in data --- Knowledge discovery in databases --- Mining, Data --- Database searching --- Machine vision --- Vision, Computer --- Artificial intelligence --- Pattern recognition systems --- Bio-informatics --- Biological informatics --- Information science --- Computational biology --- Systems biology --- Data processing --- Information storage and retrieval systems. --- Automatic data storage --- Automatic information retrieval --- Automation in documentation --- Computer-based information systems --- Data processing systems --- Data storage and retrieval systems --- Discovery systems, Information --- Information discovery systems --- Information processing systems --- Information retrieval systems --- Machine data storage and retrieval --- Mechanized information storage and retrieval systems --- Computer systems --- Electronic information resources --- Data libraries --- Digital libraries --- Information organization --- Information retrieval --- Optical data processing. --- Bioinformatics . --- Computational biology . --- Bioinformatics --- Optical computing --- Visual data processing --- Bionics --- Electronic data processing --- Integrated optics --- Photonics --- Computers --- Optical equipment --- Information organization. --- Information storage and retrieval --- Organization of information --- Information storage and retrieval systems --- Data centers

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This timely text/reference presents a broad overview of advanced deep learning architectures for learning effective feature representation for perceptual and biometrics-related tasks. The text offers a showcase of cutting-edge research on the use of convolutional neural networks (CNN) in face, iris, fingerprint, and vascular biometric systems, in addition to surveillance systems that use soft biometrics. Issues of biometrics security are also examined. Topics and features: Addresses the application of deep learning to enhance the performance of biometrics identification across a wide range of different biometrics modalities Revisits deep learning for face biometrics, offering insights from neuroimaging, and provides comparison with popular CNN-based architectures for face recognition Examines deep learning for state-of-the-art latent fingerprint and finger-vein recognition, as well as iris recognition Discusses deep learning for soft biometrics, including approaches for gesture-based identification, gender classification, and tattoo recognition Investigates deep learning for biometrics security, covering biometrics template protection methods, and liveness detection to protect against fake biometrics samples Presents contributions from a global selection of pre-eminent experts in the field representing academia, industry and government laboratories Providing both an accessible introduction to the practical applications of deep learning in biometrics, and a comprehensive coverage of the entire spectrum of biometric modalities, this authoritative volume will be of great interest to all researchers, practitioners and students involved in related areas of computer vision, pattern recognition and machine learning. Dr. Bir Bhanu is Bourns Presidential Chair, Distinguished Professor of Electrical and Computer Engineering and the Director of the Center for Research in Intelligent Systems at the University of California at Riverside, USA. Some of his other Springer publications include the titles Video Bioinformatics, Distributed Video Sensor Networks, and Human Recognition at a Distance in Video. Dr. Ajay Kumar is an Associate Professor in the Department of Computing at the Hong Kong Polytechnic University.

Biometric identification. --- Machine learning. --- Learning, Machine --- Biometric person authentication --- Biometrics (Identification) --- Computer science. --- Artificial intelligence. --- Biometrics (Biology). --- Computer science --- Computer mathematics. --- Computer Science. --- Artificial Intelligence (incl. Robotics). --- Biometrics. --- Mathematical Applications in Computer Science. --- Signal, Image and Speech Processing. --- Mathematics. --- Artificial intelligence --- Machine theory --- Anthropometry --- Identification --- Artificial Intelligence. --- AI (Artificial intelligence) --- Artificial thinking --- Electronic brains --- Intellectronics --- Intelligence, Artificial --- Intelligent machines --- Machine intelligence --- Thinking, Artificial --- Bionics --- Cognitive science --- Digital computer simulation --- Electronic data processing --- Logic machines --- Self-organizing systems --- Simulation methods --- Fifth generation computers --- Neural computers --- Computer science—Mathematics. --- Signal processing. --- Image processing. --- Speech processing systems. --- Computational linguistics --- Electronic systems --- Information theory --- Modulation theory --- Oral communication --- Speech --- Telecommunication --- Singing voice synthesizers --- Pictorial data processing --- Picture processing --- Processing, Image --- Imaging systems --- Optical data processing --- Processing, Signal --- Information measurement --- Signal theory (Telecommunication) --- Computer mathematics --- Mathematics --- Biological statistics --- Biology --- Biometrics (Biology) --- Biostatistics --- Biomathematics --- Statistics --- Statistical methods --- Biometry.

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Mathematical statistics --- Neuropathology --- Electronics --- Artificial intelligence. Robotics. Simulation. Graphics --- Computer. Automation --- patroonherkenning --- DIP (documentimage processing) --- beeldverwerking --- neurologie --- factoranalyse --- grafische vormgeving --- informatica --- elektronica --- KI (kunstmatige intelligentie) --- robots --- AI (artificiële intelligentie)

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This timely text/reference presents a broad overview of advanced deep learning architectures for learning effective feature representation for perceptual and biometrics-related tasks. The text offers a showcase of cutting-edge research on the use of convolutional neural networks (CNN) in face, iris, fingerprint, and vascular biometric systems, in addition to surveillance systems that use soft biometrics. Issues of biometrics security are also examined. Topics and features: Addresses the application of deep learning to enhance the performance of biometrics identification across a wide range of different biometrics modalities Revisits deep learning for face biometrics, offering insights from neuroimaging, and provides comparison with popular CNN-based architectures for face recognition Examines deep learning for state-of-the-art latent fingerprint and finger-vein recognition, as well as iris recognition Discusses deep learning for soft biometrics, including approaches for gesture-based identification, gender classification, and tattoo recognition Investigates deep learning for biometrics security, covering biometrics template protection methods, and liveness detection to protect against fake biometrics samples Presents contributions from a global selection of pre-eminent experts in the field representing academia, industry and government laboratories Providing both an accessible introduction to the practical applications of deep learning in biometrics, and a comprehensive coverage of the entire spectrum of biometric modalities, this authoritative volume will be of great interest to all researchers, practitioners and students involved in related areas of computer vision, pattern recognition and machine learning. Dr. Bir Bhanu is Bourns Presidential Chair, Distinguished Professor of Electrical and Computer Engineering and the Director of the Center for Research in Intelligent Systems at the University of California at Riverside, USA. Some of his other Springer publications include the titles Video Bioinformatics, Distributed Video Sensor Networks, and Human Recognition at a Distance in Video. Dr. Ajay Kumar is an Associate Professor in the Department of Computing at the Hong Kong Polytechnic University.

Mathematics --- Biomathematics. Biometry. Biostatistics --- Artificial intelligence. Robotics. Simulation. Graphics --- Computer. Automation --- patroonherkenning --- beeldverwerking --- body art --- biomathematica --- spraaktechnologie --- bio-informatica --- gezichtsherkenning (informatica) --- machine learning --- deep learning --- biostatistiek --- informatica --- biometrie --- wiskunde --- KI (kunstmatige intelligentie) --- signaalverwerking --- AI (artificiële intelligentie)