Correlation is a robust and general technique for pattern recognition and is used in many applications, such as automatic target recognition, biometric recognition and optical character recognition. The design, analysis and use of correlation pattern recognition algorithms requires background information, including linear systems theory, random variables and processes, matrix/vector methods, detection and estimation theory, digital signal processing and optical processing. This book provides a needed review of this diverse background material and develops the signal processing theory, the pattern recognition metrics, and the practical application know-how from basic premises. It shows both digital and optical implementations. It also contains technology presented by the team that developed it and includes case studies of significant interest, such as face and fingerprint recognition. Suitable for graduate students taking courses in pattern recognition theory, whilst reaching technical levels of interest to the professional practitioner.

This book constitutes the refereed proceedings of the 6th International Workshop on Structural and Syntactical Pattern Recognition, SSPR '96, held in Leipzig, Germany in August 1996. The 36 revised full papers included together with three invited papers were carefully selected from a total of 52 submissions. The papers are organized in topical sections on grammars and languages; morphology and mathematical approaches to pattern recognition; semantic nets, relational models and graph-based methods; 2D and 3D shape recognition; document image analysis and recognition; and handwritten and printed character recognition.

This book constitutes the refereed proceedings of the Third Mexican Conference on Pattern Recognition, MCPR 2011, held in Cancun, Mexico, in June/July 2011. The 37 revised full papers were carefully reviewed and selected from 69 submissions and are organized in topical sections on pattern recognition and data mining; computer vision and robotics; image processing; neural networks and signal processing; and natural language and document processing.

This book constitutes the proceedings of the 11th Mexican Conference on Pattern Recognition, MCPR 2019, held in Querétaro, Mexico, in June 2019. The 40 papers presented in this volume were carefully reviewed and selected from 86 submissions. They were organized in topical sections named: artificial intelligence techniques and recognition; computer vision; industrial and medical applications of pattern recognition; image processing and analysis; pattern recognition techniques; signal processing and analysis; natural language, and processing and recognition.

The very significant advances in computer vision and pattern recognition and their applications in the last few years reflect the strong and growing interest in the field as well as the many opportunities and challenges it offers. The second edition of this handbook represents both the latest progress and updated knowledge in this dynamic field. The applications and technological issues are particularly emphasized in this edition to reflect the wide applicability of the field in many practical problems. To keep the book in a single volume, it is not possible to retain all chapters of the first edition. However, the chapters of both editions are well written for permanent reference. This indispensable handbook will continue to serve as an authoritative and comprehensive guide in the field.

The 13-volume set LNCS 14425-14437 constitutes the refereed proceedings of the 6th Chinese Conference on Pattern Recognition and Computer Vision, PRCV 2023, held in Xiamen, China, during October 13–15, 2023. The 532 full papers presented in these volumes were selected from 1420 submissions. The papers have been organized in the following topical sections: Action Recognition, Multi-Modal Information Processing, 3D Vision and Reconstruction, Character Recognition, Fundamental Theory of Computer Vision, Machine Learning, Vision Problems in Robotics, Autonomous Driving, Pattern Classification and Cluster Analysis, Performance Evaluation and Benchmarks, Remote Sensing Image Interpretation, Biometric Recognition, Face Recognition and Pose Recognition, Structural Pattern Recognition, Computational Photography, Sensing and Display Technology, Video Analysis and Understanding, Vision Applications and Systems, Document Analysis and Recognition, Feature Extraction and Feature Selection, Multimedia Analysis and Reasoning, Optimization and Learning methods, Neural Network and Deep Learning, Low-Level Vision and Image Processing, Object Detection, Tracking and Identification, Medical Image Processing and Analysis.

The two-volume set LNCS 3522 and 3523 constitutes the refereed proceedings of the Second Iberian Conference on Pattern Recognition and Image Analysis, IbPRIA 2005, held in Estoril, Portugal in June 2005. The 170 revised full papers presented were carefully reviewed and selected from 292 submissions. The papers are organized in topical sections on computer vision, shape and matching, image and video processing, image and video coding, face recognition, human activity analysis, surveillance, robotics, hardware architectures, statistical pattern recognition, syntactical pattern recognition, image analysis, document analysis, bioinformatics, medical imaging, biometrics, speech recognition, natural language analysis, and applications.