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This important text/reference presents the first dedicated review of techniques for contactless 3D fingerprint identification, including novel and previously unpublished research. The text provides a systematic introduction to 3D fingerprint identification, covering the latest advancements in contactless 2D and 3D sensing technologies, and detailed discussions on each key aspect in the development of an effective 3D fingerprint identification system. Topics and features: Introduces the key concepts and trends in the acquisition and identification of fingerprint images, and a range of 3D fingerprint imaging techniques Proposes a low-cost method for online 3D fingerprint image acquisition, and an efficient 3D fingerprint imaging approach using coloured photometric stereo Describes pre-processing operations on point cloud 3D fingerprint data, and explains the specialized operations for reconstructing 3D fingerprints from live finger scans Examines the representation of minutiae in 3D space, providing details on recovering these features from point cloud data, and on matching such 3D minutiae templates Reviews various 3D fingerprint matching methods, including binary surface code-based approaches and a tetrahedron-based matching approach Discusses the uniqueness of 3D fingerprints, evaluating the benefits of employing 3D fingerprint identification over conventional 2D fingerprint techniques This unique work is a must-read for all researchers seeking to make further advances in this area, towards the exciting opportunities afforded by contactless 3D fingerprint identification for improving the hygiene, user convenience, and matching accuracy of fingerprint biometric technologies. Dr. Ajay Kumar is an Associate Professor in the Department of Computing at the Hong Kong Polytechnic University. He has previously served as an Assistant Professor at the Department of Electrical Engineering, IIT Delhi. He is a Fellow of IEEE and IAPR. His other publications include the Springer title Deep Learning for Biometrics.

Fingerprints --- Technological innovations. --- Dactylography --- Dactyloscopy --- Finger marks --- Finger-printing --- Finger prints --- Fingerprinting --- Anthropometry --- Dermatoglyphics --- Biometrics. --- Artificial intelligence. --- Engineering. --- Computers --- Artificial Intelligence. --- Computational Intelligence. --- Legal Aspects of Computing. --- Law and legislation. --- Cyberspace --- Construction --- Industrial arts --- Technology --- 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 --- Machine theory --- Self-organizing systems --- Simulation methods --- Fifth generation computers --- Neural computers --- Law and legislation --- Biometrics (Biology). --- Computational intelligence. --- Computers. --- Automatic computers --- Automatic data processors --- Computer hardware --- Computing machines (Computers) --- Electronic calculating-machines --- Electronic computers --- Hardware, Computer --- Computer systems --- Cybernetics --- Calculators --- Intelligence, Computational --- Artificial intelligence --- Soft computing --- Biological statistics --- Biology --- Biometrics (Biology) --- Biostatistics --- Biomathematics --- Statistics --- Statistical methods

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This important text/reference presents the first dedicated review of techniques for contactless 3D fingerprint identification, including novel and previously unpublished research. The text provides a systematic introduction to 3D fingerprint identification, covering the latest advancements in contactless 2D and 3D sensing technologies, and detailed discussions on each key aspect in the development of an effective 3D fingerprint identification system. Topics and features: Introduces the key concepts and trends in the acquisition and identification of fingerprint images, and a range of 3D fingerprint imaging techniques Proposes a low-cost method for online 3D fingerprint image acquisition, and an efficient 3D fingerprint imaging approach using coloured photometric stereo Describes pre-processing operations on point cloud 3D fingerprint data, and explains the specialized operations for reconstructing 3D fingerprints from live finger scans Examines the representation of minutiae in 3D space, providing details on recovering these features from point cloud data, and on matching such 3D minutiae templates Reviews various 3D fingerprint matching methods, including binary surface code-based approaches and a tetrahedron-based matching approach Discusses the uniqueness of 3D fingerprints, evaluating the benefits of employing 3D fingerprint identification over conventional 2D fingerprint techniques This unique work is a must-read for all researchers seeking to make further advances in this area, towards the exciting opportunities afforded by contactless 3D fingerprint identification for improving the hygiene, user convenience, and matching accuracy of fingerprint biometric technologies. Dr. Ajay Kumar is an Associate Professor in the Department of Computing at the Hong Kong Polytechnic University. He has previously served as an Assistant Professor at the Department of Electrical Engineering, IIT Delhi. He is a Fellow of IEEE and IAPR. His other publications include the Springer title Deep Learning for Biometrics.

Biomathematics. Biometry. Biostatistics --- Applied physical engineering --- Artificial intelligence. Robotics. Simulation. Graphics --- Computer. Automation --- neuronale netwerken --- fuzzy logic --- cybernetica --- biomathematica --- cloud computing --- deep learning --- biostatistiek --- informatica --- biometrie --- KI (kunstmatige intelligentie) --- ingenieurswetenschappen --- computercriminaliteit --- AI (artificiële intelligentie)

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This first volume of a two-volume work presents the manifold applications of beneficial microbes and microbiomes in plant growth promotion, in enhancing crop resilience and in control of phytopathogens through microbial antagonists. In-depth insights into latest technologies such as biopriming of seeds and soil inoculation of rhizosphere microorganisms are provided. The two-volume work "Microbial Biocontrol" introduces mechanisms of plant-microbe interactions and explores latest strategies of how microbes can be applied in biocontrol and management of plant pathogens, replacing chemical fertilizers and pesticides. The book covers different groups of microorganisms such as bacteria, fungi, but also the interplay of entire microbiomes, and reviews their specific benefits in crop growth promotion, in enhancing the plants' tolerance against biotic and abiotic stress as well as in post-harvest management of various plant diseases. Novel tools such as CRISPR/Cas9 and microbe derived nanoparticles are also addressed besides the legal aspects of biocontrol applications. Today, rising global population and changing climatic conditions emerge as a major challenge for agronomist farmers and researchers in fulfilling the requirements of global food production. The conventional agricultural practices utilize undistributed use of chemical fertilizers and pesticides to enhance growth and yield of agricultural products and fresh foods, but their extensive and continuous use have led to a range of negative consequences on the food quality and safety, to environment as well as to human and animal health. Microbial biocontrol applications are presented as a solution, paving the way to a sustainable agriculture in compliance with the UN Sustainable Development Goals (SDG). The book addresses researchers in academia and agriculture.

Nutritionary hygiene. Diet --- Food science and technology --- voedselmicrobiologie --- voedingstechnologie

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This book, authored by Ajay Kumar, delves into the advanced methodologies of iris and periocular recognition using deep learning techniques. It discusses various innovations in biometric systems, focusing on areas such as iris segmentation and recognition, network architectures for optimized iris templates, and feature encoding. The book examines the effectiveness of convolutional neural networks in enhancing recognition accuracy and explores dynamic iris recognition frameworks. It is intended for researchers and practitioners in the field of biometrics and computer vision, offering insights into the latest trends and challenges in iris recognition technologies.

Biometric identification. --- Iris (Eye) --- Biometric identification