Books in Computer vision and pattern recognition

51-60 of 71 results in All results

Handbook of Image and Video Processing

• 2nd Edition
• July 21, 2010
• Alan C. Bovik
• English
• eBook 978-0-08-053361-2

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55% new material in the latest edition of this “must-have” for students and practitioners of image & video processing!This Handbook is intended to serve as the basic reference point on image and video processing, in the field, in the research laboratory, and in the classroom. Each chapter has been written by carefully selected, distinguished experts specializing in that topic and carefully reviewed by the Editor, Al Bovik, ensuring that the greatest depth of understanding be communicated to the reader. Coverage includes introductory, intermediate and advanced topics and as such, this book serves equally well as classroom textbook as reference resource. • Provides practicing engineers and students with a highly accessible resource for learning and using image/video processing theory and algorithms • Includes a new chapter on image processing education, which should prove invaluable for those developing or modifying their curricula • Covers the various image and video processing standards that exist and are emerging, driving today’s explosive industry • Offers an understanding of what images are, how they are modeled, and gives an introduction to how they are perceived • Introduces the necessary, practical background to allow engineering students to acquire and process their own digital image or video data • Culminates with a diverse set of applications chapters, covered in sufficient depth to serve as extensible models to the reader’s own potential applications About the Editor… Al Bovik is the Cullen Trust for Higher Education Endowed Professor at The University of Texas at Austin, where he is the Director of the Laboratory for Image and Video Engineering (LIVE). He has published over 400 technical articles in the general area of image and video processing and holds two U.S. patents. Dr. Bovik was Distinguished Lecturer of the IEEE Signal Processing Society (2000), received the IEEE Signal Processing Society Meritorious Service Award (1998), the IEEE Third Millennium Medal (2000), and twice was a two-time Honorable Mention winner of the international Pattern Recognition Society Award. He is a Fellow of the IEEE, was Editor-in-Chief, of the IEEE Transactions on Image Processing (1996-2002), has served on and continues to serve on many other professional boards and panels, and was the Founding General Chairman of the IEEE International Conference on Image Processing which was held in Austin, Texas in 1994.

Introduction to Pattern Recognition

• 1st Edition
• March 3, 2010
• Sergios Theodoridis + 3 more
• English
• Paperback 978-0-12-374486-9

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• eBook 978-0-08-092275-1

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Introduction to Pattern Recognition: A Matlab Approach is an accompanying manual to Theodoridis/Koutroumbas' Pattern Recognition. It includes Matlab code of the most common methods and algorithms in the book, together with a descriptive summary and solved examples, and including real-life data sets in imaging and audio recognition. This text is designed for electronic engineering, computer science, computer engineering, biomedical engineering and applied mathematics students taking graduate courses on pattern recognition and machine learning as well as R&D engineers and university researchers in image and signal processing/analyisis, and computer vision.

Pattern Recognition

• 4th Edition
• October 20, 2008
• Konstantinos Koutroumbas + 1 more
• English
• Hardback 978-1-59749-272-0

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• eBook 978-0-08-094912-3

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This book considers classical and current theory and practice, of supervised, unsupervised and semi-supervised pattern recognition, to build a complete background for professionals and students of engineering. The authors, leading experts in the field of pattern recognition, have provided an up-to-date, self-contained volume encapsulating this wide spectrum of information. The very latest methods are incorporated in this edition: semi-supervised learning, combining clustering algorithms, and relevance feedback. · Thoroughly developed to include many more worked examples to give greater understanding of the various methods and techniques· Many more diagrams included--now in two color--to provide greater insight through visual presentation· Matlab code of the most common methods are given at the end of each chapter.· More Matlab code is available, together with an accompanying manual, via this site · Latest hot topics included to further the reference value of the text including non-linear dimensionality reduction techniques, relevance feedback, semi-supervised learning, spectral clustering, combining clustering algorithms.· An accompanying book with Matlab code of the most common methods and algorithms in the book, together with a descriptive summary, and solved examples including real-life data sets in imaging, and audio recognition. The companion book will be available separately or at a special packaged price (ISBN: 9780123744869).

Mathematical Optimization in Computer Graphics and Vision

• 1st Edition
• April 18, 2008
• Luiz Velho + 3 more
• English
• Hardback 978-0-12-715951-5

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• eBook 978-0-08-087858-4

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Mathematical optimization is used in nearly all computer graphics applications, from computer vision to animation. This book teaches readers the core set of techniques that every computer graphics professional should understand in order to envision and expand the boundaries of what is possible in their work. Study of this authoritative reference will help readers develop a very powerful tool- the ability to create and decipher mathematical models that can better realize solutions to even the toughest problems confronting computer graphics community today.

Pattern Recognition in Industry

• 1st Edition
• March 30, 2005
• Phiroz Bhagat
• English
• Hardback 978-0-08-044538-0

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• eBook 978-0-08-045602-7

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"Find it hard to extract and utilise valuable knowledge from the ever-increasing data deluge?" If so, this book will help, as it explores pattern recognition technology and its concomitant role in extracting useful information to build technical and business models to gain competitive industrial advantage.*Based on first-hand experience in the practice of pattern recognition technology and its development and deployment for profitable application in Industry.Phiroz Bhagat is often referred to as the pioneer of neural net and pattern recognition technology, and is uniquely qualified to write this book. He brings more than two decades of experience in the "real-world" application of cutting-edge technology for competitive advantage in industry.Two wave fronts are upon us today: we are being bombarded by an enormous amount of data, and we are confronted by continually increasing technical and business advances.Ideally, the endless stream of data should be one of our major assets. However, this potential asset often tends to overwhelm rather than enrich. Competitive advantage depends on our ability to extract and utilize nuggets of valuable knowledge and insight from this data deluge. The challenges that need to be overcome include the under-utilization of available data due to competing priorities, and the separate and somewhat disparate existing data systems that have difficulty interacting with each other.Conventional approaches to formulating models are becoming progressively more expensive in time and effort. To impart a competitive edge, engineering science in the 21st century needs to augment traditional modelling processes by auto-classifying and self-organizing data; developing models directly from operating experience, and then optimizing the results to provide effective strategies and operating decisions. This approach has wide applicability; in areas ranging from manufacturing processes, product performance and scientific research, to financial and business fields.This monograph explores pattern recognition technology, and its concomitant role in extracting useful knowledge to build technical and business models directly from data, and in optimizing the results derived from these models within the context of delivering competitive industrial advantage. It is not intended to serve as a comprehensive reference source on the subject. Rather, it is based on first-hand experience in the practice of this technology: its development and deployment for profitable application in industry. The technical topics covered in the monograph will focus on the triad of technological areas that constitute the contemporary workhorses of successful industrial application of pattern recognition. These are: systems for self-organising data; data-driven modelling; and genetic algorithms as robust optimizers.

Pattern Recognition and Signal Analysis in Medical Imaging

• 1st Edition
• October 31, 2003
• Anke Meyer-Baese + 1 more
• English
• eBook 978-0-08-046998-0

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Medical Imaging has become one of the most important visualization and interpretation methods in biology and medecine over the past decade. This time has witnessed a tremendous development of new, powerful instruments for detecting, storing, transmitting, analyzing, and displaying medical images. This has led to a huge growth in the application of digital processing techniques for solving medical problems. Design, implementation, and validation of complex medical systems requires a tight interdisciplinary collaboration between physicians and engineers because poor image quality leads to problematic feature extraction, analysis, and recognition in medical application. Therefore, much of the research done today is geared towards improvement of imperfect image material. This important book by academic authority Anke Meyer-Baese compiles, organizes and explains a complete range of proven and cutting-edge methods, which are playing a leading role in the improvement of image quality, analysis and interpretation in modern medical imaging. These methods offer fresh tools of hope for physicians investigating a vast number of medical problems for which classical methods prove insufficient.

De-interlacing

• 1st Edition
• Volume 9
• October 2, 2000
• E.B. Bellers + 1 more
• English
• eBook 978-0-08-050386-8

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'To interlace or not to interlace' is a hot issue currently. Traditionally interlace has been part of the video standard as it reduces the transmission and display demands, while hardly affecting the perceived quality of the pictures.With the current explosion of new video formats due to emerging technologies as multimedia PC's, videotelephony and flat matrix display the question whether or not interlace is a relict from the past is more relevant than ever.This book provides a broad overview of advanced motion estimation and de-interlacing techniques to enable a profound scientific basis for answering the above question. An extensive evaluation of the algorithms, including many screen photographs is an imt part of the book. But also system questions, such as whether interlace is a good choice in combination with modern video compression methods (MPEG), and which currently would be the optional choice for a display format are extensively treated.The combination of scientific profoundness and completions, with the focus on practical hot issues, makes the book unique in its kind.

Image and Video Databases: Restoration, Watermarking and Retrieval

• 1st Edition
• Volume 8
• June 14, 2000
• A. Hanjalic + 4 more
• English
• eBook 978-0-08-050847-4

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This book provides an in-depth treatment of the three important topics related to image and video databases: restoration, watermarking and retrieval. It is the result of the participation of the Delft University of Technology in the European Union ACTS program, a pre-competitive R&D program on Advanced Communications Technologies and Services (1994-1998). In particular the book has benefited from participation in the AURORA and SMASH projects respectively automated film and video restoration and storage for multimedia systems (watermarking & retrieval).

Computer Vision and Applications

• 1st Edition
• April 24, 2000
• Bernd Jahne
• English
• Hardback 978-0-12-379777-3

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• eBook 978-0-08-050262-5

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Based on the highly successful 3-volume reference Handbook of Computer Vision and Applications, this concise edition covers in a single volume the entire spectrum of computer vision ranging form the imaging process to high-end algorithms and applications. This book consists of three parts, including an application gallery.

A Computational Framework for Segmentation and Grouping

• 1st Edition
• March 1, 2000
• G. Medioni + 2 more
• English
• eBook 978-0-08-052948-6

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This book represents a summary of the research we have been conducting since the early 1990s, and describes a conceptual framework which addresses some current shortcomings, and proposes a unified approach for a broad class of problems. While the framework is defined, our research continues, and some of the elements presented here will no doubt evolve in the coming years.It is organized in eight chapters. In the Introduction chapter, we present the definition of the problems, and give an overview of the proposed approach and its implementation. In particular, we illustrate the limitations of the 2.5D sketch, and motivate the use of a representation in terms of layers instead.In chapter 2, we review some of the relevant research in the literature. The discussion focuses on general computational approaches for early vision, and individual methods are only cited as references. Chapter 3 is the fundamental chapter, as it presents the elements of our salient feature inference engine, and their interaction. It introduced tensors as a way to represent information, tensor fields as a way to encode both constraints and results, and tensor voting as the communication scheme. Chapter 4 describes the feature extraction steps, given the computations performed by the engine described earlier. In chapter 5, we apply the generic framework to the inference of regions, curves, and junctions in 2-D. The input may take the form of 2-D points, with or without orientation. We illustrate the approach on a number of examples, both basic and advanced. In chapter 6, we apply the framework to the inference of surfaces, curves and junctions in 3-D. Here, the input consists of a set of 3-D points, with or without as associated normal or tangent direction. We show a number of illustrative examples, and also point to some applications of the approach. In chapter 7, we use our framework to tackle 3 early vision problems, shape from shading, stereo matching, and optical flow computation. In chapter 8, we conclude this book with a few remarks, and discuss future research directions.We include 3 appendices, one on Tensor Calculus, one dealing with proofs and details of the Feature Extraction process, and one dealing with the companion software packages.