This book presents state-of-the-art methodologies and a comprehensive introduction to the recognition and representation of species and individual animals based on their physiological and phenotypic appearances, biometric characteristics, and morphological image patterns. It provides in-depth coverage of this emerging area, with an emphasis on the design and analysis techniques used in visual animal biometrics-based recognition systems.

The book offers a comprehensive introduction to visual animal biometrics, addressing a range of recent advances and practices like sensing, feature extraction, feature selection and representation, matching, indexing of feature sets, and animal biometrics-based multimodal systems. It provides authoritative information on all the major concepts, as well as highly specific topics, e.g. the identification of cattle based on their muzzle point image pattern and face images to prevent false insurance claims, or the monitoring and registration of animals based on their biometric features.

As such, the book provides a sound platform for understanding the Visual Animal Biometrics paradigm, a vital catalyst for researchers in the field, and a valuable guide for professionals. In addition, it can help both private and public organizations adapt and enhance their classical animal recognition systems.

Discusses recent and future advancements in visual animal biometrics Presents novel and recent detection and representation-based machine learning and computer vision algorithms for the recognition of animals based on their phenotypic appearances, morphological image patterns, and biometric characteristics Highlights several potential visual animal biometrics techniques, as well as their applications Presents important fundamentals of fingerprint-based recognition and representation Establishes secure recognition systems for cattle based on their faces and muzzles Points out major shortcomings of traditional non-animal-biometrics-based recognition and monitoring systems

Autorentext

Dr Santosh Kumar Dr Santosh Kumar is an Assistant Professor of Computer Science and Engineering. Prior to joining the International Institute of Information Technology-Naya Raipur (IIIT-Naya Raipur), Chhattisgarh, he was a Ph.D. scholar at the Department of Computer Science and Engineering, Indian Institute of Technology (Banaras Hindu University) (IIT (BHU)), Varanasi, Uttar Pradesh, India. He is a member of the Computer Society and the Association for Computing Machinery. He has published and presented over 25 research papers including book chapters in reputed journals and at numerous reputed national and international conferences. His research interests include Animal Biometrics, Computer Vision, Machine Learning, Pattern Recognition, Wireless Sensors, and the Internet of Things (IoT). Dr Sanjay Kumar Singh Dr Sanjay Kumar Singh completed his B.Tech. in Computer Engineering, M.Tech. in Computer Applications and Ph.D. in Computer Science and Engineering. Currently, he is an Associate Professor at the Department of Computer Science and Engineering, Indian Institute of Technology (Banaras Hindu University), (IIT (BHU)), Varanasi, Uttar Pradesh, India. He is a Certified Novell Engineer (CNE) and Certified Novell Administrator (CNA) from Novell Netware, USA. He is a member of LIMSTE, the IEE, the International Association of Engineers and the ISCE. His research areas include Biometrics, Computer Vision, Image Processing, Video Processing, Pattern Recognition, Artificial Intelligence and Big Data. Dr Rishav Singh Dr Rishav Singh received his B.Tech. from C. V. Raman College of Engineering (CVRCE), Orissa, India, in 2009. He completed his M.Tech. at Jaypee University of Information Technology (JUIT), India, in 2011 and his Ph.D. at the Indian Institute of Technology (Indian School of Mines) (IIT(ISM)), Dhanbad, in 2017. He has extensive IT experience, with proven expertise in the full software development lifecycle including requirement analysis, designing, coding, deploying the code in different environments and implementation of software applications using R, Cassandra, Machine Learning, Cloudera Hadoop (Map-Reduce), HBase and Hive. His research interests include Big Data & Analytics, Machine Learning, Biometrics and Image Processing. Dr Amit Kumar Singh Dr Amit Kumar Singh is currently working as an Assistant Professor (Senior Grade) at the Department of Computer Science and Engineering, Jaypee University of Information Technology (JUIT), India. He completed his Ph.D. degree at the Department of Computer Engineering, National Institute of Technology (NIT), Kurukshetra in 2015. Recently, Dr Singh was appointed as Associate Editor of IEEE Access and Multimedia Tools and Applications (MTAP), Springer. He has published and presented over 50 research papers in reputed journals and at various national and international conferences. His important research contributions include developing watermarking methods that offer a good trade-off between major parameters i.e., perceptual quality, robustness, embedding capacity and the security of watermark embedding into digital images. His research interests include Data Hiding, Biometrics and Cryptography.

Inhalt

Chapter 1. Introduction.- Chapter 2. Animal Biometric System.- Chapter 3. Animal Biometrics based Approaches.- Chapter 4. Classical Animal Recognition Methodology and Frameworks.- Chapter 5. Animal Biometrics based Recognition Systems (Based on Current State of the Art Approaches).- Chapter 6. Representation and Identification of Species: Computer Vision and Pattern Recognition Models.- Chapter 7. Emerging Trends and Future Challenges.