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.

Medical imaging is an important topic and plays a key role in robust diagnosis and patient care. It has experienced an explosive growth over the last few years due to imaging modalities such as X-rays, computed tomography (CT), magnetic resonance (MR) imaging, and ultrasound. This book focuses primarily on model-based segmentation techniques, which are applied to cardiac, brain, breast and microscopic cancer cell imaging. It includes contributions from authors working in industry and academia, and presents new material.

This book features a collection of articles presented at the 2007 Workshop on Advances in Pattern Recognition, which was organized in conjunction with the 5th International Summer School on Pattern Recognition. It provides readers with the state-of-the-art algorithms in the area of pattern recognition as well as a presentation of the cutting edge applications within the field.

International Conference on Advances in Pattern Recognition (ICAPR 98) at Plymouth represents an important meeting for advanced research in pattern recognition. There is considerable interest in the areas of image processing, medical imaging, speech recognition, document analysis and character recognition, fuzzy data analysis and neural networks. ICAPR 98 is aimed at providing an international platform for invited research in this multi-disciplinary area. It is expected that the conference will grow in future years to include more research contributions that detail state-of the-art research in pattern recognition. ICAPR 98 attracted contributions from different countries of the highest quality. I should like to thank the programme and organising committee for doing an excellent job in organising this conference. The peer reviewed nature of the conference ensured high quality publications in these proceedings. My personal thanks to Mrs. Barbara Davies who served as conference secretary and worked tirelessly in organising the conference. I thank the organising chair for the local arrangements and our should also key-note, plenary and tutorial speakers for their valuable contributions to the conference. I also thank Springer-Verlag for publishing these proceedings that will be a valuable source of research reference for the readers. Finally, I thank all participants who made this conference successful."

This LNCS volume contains the papers presented at the 3rd International C- ferenceonAdvances in PatternRecognition(ICAPR2005)organizedin August, 2005 in the beautiful city of Bath, UK. The conference was ?rst organized in November 1998 in Plymouth, UK and subsequently in March 2001 in Rio de Janeiro, Brazil. The conference encouraged papers that made signi?cant th- reticalandapplication-basedcontributions inpatternrecognition. The emphasis was on an open exchange of ideas and shared learning. The papers submitted to ICAPR 2005 were thoroughly reviewed by up to three referees per paper and less than 40% of the submitted papers were accepted. The papers have been ?nally published as two volumes of LNCS and these are organized under the themes of Pattern Recognition and Data Mining (which included papers from the trackson PatternRecognition Methods, Knowledgeand Learning, and Data Mining), and Pattern Recognition and Image Analysis (which included papers from the Applications track). From the conference technical programme point of view, the ?rst volume contains papers on pattern recognition, data mining, signal processing and OCR/document analysis. The second volume contains - pers from the Workshop on Pattern Recognition for Crime Prevention, Security and Surveillance, Biometrics, Image Processing and Medical Imaging. ICAPR 2005was run in parallel with the InternationalWorkshop on Pattern Recognition for Crime Prevention, Security and Surveillance that was organized onthe22ndofAugust,2005. Thisworkshopbroughttogethera number ofexc- lent papers that focussed on how pattern recognition techniques can be used to developsystemsthathelpwithcrimepreventionanddetection. Onthesameday, a number of tutorials were also organized

This LNCS volume contains the papers presented at the 3rd International C- ferenceonAdvances in PatternRecognition(ICAPR2005)organizedin August, 2005 in the beautiful city of Bath, UK. The conference was ?rst organized in November 1998 in Plymouth, UK and subsequently in March 2001 in Rio de Janeiro, Brazil. The conference encouraged papers that made signi?cant th- reticalandapplication-basedcontributions inpatternrecognition. The emphasis was on an open exchange of ideas and shared learning. The papers submitted to ICAPR 2005 were thoroughly reviewed by up to three referees per paper and less than 40% of the submitted papers were accepted. The papers have been ?nally published as two volumes of LNCS and these are organized under the themes of Pattern Recognition and Data Mining (which included papers from the trackson PatternRecognition Methods, Knowledgeand Learning, and Data Mining), and Pattern Recognition and Image Analysis (which included papers from the Applications track). From the conference technical programme point of view, the ?rst volume contains papers on pattern recognition, data mining, signal processing and OCR/document analysis. The second volume contains - pers from the Workshop on Pattern Recognition for Crime Prevention, Security and Surveillance, Biometrics, Image Processing and Medical Imaging. ICAPR 2005was run in parallel with the InternationalWorkshop on Pattern Recognition for Crime Prevention, Security and Surveillance that was organized onthe22ndofAugust,2005. Thisworkshopbroughttogethera number ofexc- lent papers that focussed on how pattern recognition techniques can be used to developsystemsthathelpwithcrimepreventionanddetection. Onthesameday, a number of tutorials were also organized

This book constitutes the refereed proceedings of the Second International Conference on Advances in Pattern Recognition, ICAPR 2001, held in Rio de Janeiro, Brazil in March 2001.The 40 revised full papers presented together with three invited papers and two tutorial presentations were carefully reviewed and selected for inclusion in the proceedings. The book is organized in topical sections on neural networks and computational intelligence, character recognition and document analysis, feature selection and analysis, pattern recognition and classification, image and signal processing applications, and image feature analysis and retrieval.

Medical imaging is an important topic which is generally recognised as key to better diagnosis and patient care. It has experienced an explosive growth over the last few years due to imaging modalities such as X-rays, computed tomography (CT), magnetic resonance (MR) imaging, and ultrasound.This book focuses primarily on state-of-the-art model-based segmentation techniques which are applied to cardiac, brain, breast and microscopic cancer cell imaging. It includes contributions from authors based in both industry and academia and presents a host of new material including algorithms for:- brain segmentation applied to MR;- neuro-application using MR; - parametric and geometric deformable models for brain segmentation;- left ventricle segmentation and analysis using least squares and constrained least squares models for cardiac X-rays; - left ventricle analysis in echocardioangiograms;- breast lesion detection in digital mammograms;detection of cells in cell images.As an overview of the latest techniques, this book will be of particular interest to students and researchers in medical engineering, image processing, computer graphics, mathematical modelling and data analysis. It will also be of interest to researchers in the fields of mammography, cardiology, pathology and neurology.