A comprehensive guide to the essential principles of image processing and pattern recognition Techniques and applications in the areas of image processing and pattern recognition are growing at an unprecedented rate. Containing the latest state-of-the-art developments in the field, Image Processing and Pattern Recognition presents clear explanations of the fundamentals as well as the most recent applications. It explains the essential principles so readers will not only be able to easily implement the algorithms and techniques, but also lead themselves to discover new problems and applications. Unlike other books on the subject, this volume presents numerous fundamental and advanced image processing algorithms and pattern recognition techniques to illustrate the framework. Scores of graphs and examples, technical assistance, and practical tools illustrate the basic principles and help simplify the problems, allowing students as well as professionals to easily grasp even complicated theories. It also features unique coverage of the most interesting developments and updated techniques, such as image watermarking, digital steganography, document processing and classification, solar image processing and event classification, 3-D Euclidean distance transformation, shortest path planning, soft morphology, recursive morphology, regulated morphology, and sweep morphology. Additional topics include enhancement and segmentation techniques, active learning, feature extraction, neural networks, and fuzzy logic. Featuring supplemental materials for instructors and students, Image Processing and Pattern Recognition is designed for undergraduate seniors and graduate students, engineering and scientific researchers, and professionals who work in signal processing, image processing, pattern recognition, information security, document processing, multimedia systems, and solar physics.

A detailed exposition of the main areas of signal processing, this book is divided into three sections: one-dimensional signal processing and digital filters; two-dimensional signal processing and image processing; and pattern recognition.

A comprehensive guide to the essential principles of image processing and pattern recognition Techniques and applications in the areas of image processing and pattern recognition are growing at an unprecedented rate. Containing the latest state-of-the-art developments in the field, Image Processing and Pattern Recognition presents clear explanations of the fundamentals as well as the most recent applications. It explains the essential principles so readers will not only be able to easily implement the algorithms and techniques, but also lead themselves to discover new problems and applications. Unlike other books on the subject, this volume presents numerous fundamental and advanced image processing algorithms and pattern recognition techniques to illustrate the framework. Scores of graphs and examples, technical assistance, and practical tools illustrate the basic principles and help simplify the problems, allowing students as well as professionals to easily grasp even complicated theories. It also features unique coverage of the most interesting developments and updated techniques, such as image watermarking, digital steganography, document processing and classification, solar image processing and event classification, 3-D Euclidean distance transformation, shortest path planning, soft morphology, recursive morphology, regulated morphology, and sweep morphology. Additional topics include enhancement and segmentation techniques, active learning, feature extraction, neural networks, and fuzzy logic. Featuring supplemental materials for instructors and students, Image Processing and Pattern Recognition is designed for undergraduate seniors and graduate students, engineering and scientific researchers, and professionals who work in signal processing, image processing, pattern recognition, information security, document processing, multimedia systems, and solar physics.

This unique text/reference reviews the field of digital image processing from the different perspectives offered by the separate domains of signal processing and pattern recognition. The book describes a rich array of applications, representing the latest trends in industry and academic research. To inspire further interest in the field, a selection of elegant, worked-out numerical problems are also included in the text. The content is presented in an accessible manner, examining each topic in depth without assuming any prior knowledge from the reader, and providing additional background material in the appendices. Topics and features: Introduces the processes of sampling, quantization and encoding of images, as well as the operations of convolution and correlation, and the basic geometric transformations Covers image enhancement techniques in the spatial domain, the frequency domain, and the wavelet domain Describes the basics of the physics of light and color, and of the psycho-visual color system Reviews compression methods and formats for encoding images Discusses morphology-based image processing, which bridges signal processing and pattern recognition perspectives Examines state-of-the-art applications of techniques for feature extraction, selection, and reduction Investigates the modeling of object recognition in the human visual system for computer vision Provides electronic supplementary material, including MATLAB and C++ code, interactive GUI-based modules, and teaching slides at an associated website Appealing to a broad audience of students, tutors, researchers and professionals, this work offers an indispensable guide to image processing, pattern recognition and computer vision. The coverage draws upon the author's extensive experience in academic teaching and training, government R&D, and private industry.

Both pattern recognition and signal processing are rapidly growing areas. Organized with emphasis on many inter-relations between the two areas, a NATO Advanced Study Institute on Pattern Recognition and Signal Processing was held June 25th - July 4, 1978 at the E.N.S.T. (Department of Electronics) in Paris, France. This volume is the Proceedings of the Institute. It contains what I believed to be a truly outstanding collection of papers which cover all major activities in both pattern recognition and signal processing. The papers are grouped by topics as follows: I. Syntactic Methods: paper numbers 1, 2. II. Statistical Methods: paper numbers 3, 4, 5, 6. III. Detection and Estimation: paper numbers 7, 8. IV. Image Processing, Modelling, and Analysis: paper numbers 9, 10, 11, 12. V. Speech Application: paper numbers 13, 14. VI. Radar Application: paper number 15. Seismic Application: paper number 16. VII. Biomedical Application: paper numbers 17, 18, 19. VIII. IX. Reconstruction From Projections: paper numbers 20, 21- X. Signal Modelling and Application: paper numbers 22, 23, 24. XI. NATO Pattern Recognition Research Study Group Report: paper number 25. It is my strong belief that there is a need for continuing interaction between pattern recognition and signal processing. The book will serve as a useful text and reference for such a need, and for both areas. Finally on behalf of all participants of the Institute, I would like to thank Drs. T. Kester and M. N. Czdas of NATO for their support.

The aim of this book is to deal with biometrics in terms of signal and image processing methods and algorithms. This will help engineers and students working in digital signal and image processing deal with the implementation of such specific algorithms. It discusses numerous signal and image processing techniques that are very often used in biometric applications. In particular, algorithms related to hand feature extraction, speech recognition, 2D/3D face biometrics, video surveillance and other interesting approaches are presented. Moreover, in some chapters, Matlab codes are provided so that readers can easily reproduce some basic simulation results. This book is suitable for final-year undergraduate students, postgraduate students, engineers and researchers in the field of computer engineering and applied digital signal and image processing. 1. Introduction to Biometrics, Bernadette Dorizzi. 2. Introduction to 2D Face Recognition, Amine Nait-Ali and Dalila Cherifi. 3. Facial Soft Biometrics for Person Recognition, Antitza Dantcheva, Christelle Yemdji, Petros Elia and Jean-Luc Dugelay. 4. Modeling, Reconstruction and Tracking for Face Recognition, Catherine Herold, Vincent Despiegel, Stéphane Gentric, Séverine Dubuisson and Isabelle Bloch. 5. 3D Face Recognition, Mohsen Ardabilian, Przemyslaw Szeptycki, Di Huang and Liming Chen. 6. Introduction to Iris Biometrics, Kamel Aloui, Amine Nait-Ali, Régis Fournier and Saber Naceur. 7. Voice Biometrics: Speaker Verification and Identification, Foezur Chowdhury, Sid-Ahmed Selouani and Douglas O’Shaughnessy. 8. Introduction to Hand Biometrics, Régis Fournier and Amine Nait-Ali. 9. Multibiometrics, Romain Giot, Baptiste Hemery, Estelle Cherrier and Christophe Rosenberger. 10. Hidden Biometrics, Amine Nait-Ali, Régis Fournier, Kamel Aloui and Noureddine Belgacem. 11. Performance Evaluation of Biometric Systems, Mohamad El-Abed, Romain Giot, Baptiste Hemery, Julien Mahier and Christophe Rosenberger. 12. Classification Techniques for Biometrics, Amel Bouchemha, Chérif Nait-Hamoud, Amine Nait-Ali and Régis Fournier. 13. Data Cryptography, Islam Naveed and William Puech. 14. Visual Data Protection, Islam Naveed and William Puech. 15. Biometrics in Forensics, Guillaume Galou and Christophe Lambert.