Progress in Pattern Recognition

The field of pattern recognition has emerged as one of the most challenging and important endeavours in the area of information technology research. Research in the area of pattern recognition has benefits for improving many areas of human endeavour, including medicine, the economy, the environment, and security. This book presents some of the latest advances in the area of pattern recognition theory and applications. The first half of the book discusses novel pattern classification and matching schemes, and the second half describes the application of novel tools in biometrics and digital multimedia. The applications included, such as face/iris recognition, handwriting recognition, surveillance, human dynamics, sensor fusion, etc., provide a detailed insight into how to build real pattern recognition systems and how to evaluate them. Given the dynamic nature of technology evolution in this area, this book provides the latest algorithms and concepts that can be used to build real systems. Features and topics: Provides state-of-the art algorithms, as well as presents cutting-edge applications within the field Introduces achievements in theoretical pattern recognition, including statistical and Bayesian pattern recognition, structural pattern recognition, neural networks, classification and data mining, evolutionary approaches to optimisation, and knowledge based systems Offers insights and support to practitioners concerned with the state-of-the art technology in the area Progress in Pattern Recognition addresses the needs of postgraduate students, researchers, and practitioners in the areas of computer science, engineering and mathematicswhere pattern recognition techniques are widely used. Professor Sameer Singh is Director of the Research School of Informatics, Loughborough University, UK, and serves as Editor-in-Chief of the Springer journal, Pattern Analysis and Applications