Medial Representations

Mathematics, Algorithms and Applications

Author: Kaleem Siddiqi,Stephen Pizer

Publisher: Springer Science & Business Media

ISBN: 140208658X

Category: Mathematics

Page: 439

View: 1743

The last half century has seen the development of many biological or physical t- ories that have explicitly or implicitly involved medial descriptions of objects and other spatial entities in our world. Simultaneously mathematicians have studied the properties of these skeletal descriptions of shape, and, stimulated by the many areas where medial models are useful, computer scientists and engineers have developed numerous algorithms for computing and using these models. We bring this kno- edge and experience together into this book in order to make medial technology more widely understood and used. The book consists of an introductory chapter, two chapters on the major mat- matical results on medial representations, ?ve chapters on algorithms for extracting medial models from boundary or binary image descriptions of objects, and three chapters on applications in image analysis and other areas of study and design. We hope that this book will serve the science and engineering communities using medial models and will provide learning material for students entering this ?eld. We are fortunate to have recruited many of the world leaders in medial theory, algorithms, and applications to write chapters in this book. We thank them for their signi?cant effort in preparing their contributions. We have edited these chapters and have combined them with the ?ve chapters that we have written to produce an integrated whole.
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Energy Minimization Methods in Computer Vision and Pattern Recognition

8th International Conference, EMMCVPR 2011, St. Petersburg, Russia, July 25-27, 2011, Proceedings

Author: Yuri Boykov,Fredrik Kahl,Victor Lempitsky,Frank R. Schmidt

Publisher: Springer Science & Business Media

ISBN: 3642230938

Category: Computers

Page: 450

View: 9252

This book constitutes the refereed proceedings of the 8th International Workshop on Energy Minimization Methods in Computer Vision and Pattern Recognition, EMMCVPR 2011, held in St. Petersburg, Russia in July , 2011. The book presents 30 revised full papers selected from a total of 52 submissions. The book is divided in sections on discrete and continuous optimization, segmentation, motion and video, learning and shape analysis.
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Advanced Concepts for Intelligent Vision Systems

14th International Conference, ACIVS 2012, Brno, Czech Republic, September 4-7, 2012, Proceedings

Author: Jaques Blanc-Talon,Wilfried Philips,Dan Popescu,Paul Scheunders,Pavel Zemcik

Publisher: Springer

ISBN: 3642331408

Category: Computers

Page: 540

View: 8318

This book constitutes the thoroughly refereed proceedings of the 14th International Conference on Advanced Concepts for Intelligent Vision Systems, ACIVS 2012, held in Brno, Czech Republic, in September 2012. The 46 revised full papers were carefully selected from 81 submissions and deal with image analysis and computer vision with a focus on detection, recognition, tracking and identification.
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Advances in Visual Computing

10th International Symposium, ISVC 2014, Las Vegas, NV, USA, December 8-10, 2014, Proceedings

Author: George Bebis,Richard Boyle,Bahram Parvin,Darko Koracin,Ryan McMahan,Jason Jerald,Hui Zhang,Steven Drucker,Kambhamettu Chandra,El Choubassi Maha,Zhigang Deng,Mark Carlson

Publisher: Springer

ISBN: 3319143646

Category: Computers

Page: 952

View: 2736

The two volume set LNCS 8887 and 8888 constitutes the refereed proceedings of the 10th International Symposium on Visual Computing, ISVC 2014, held in Las Vegas, NV, USA. The 74 revised full papers and 55 poster papers presented together with 39 special track papers were carefully reviewed and selected from more than 280 submissions. The papers are organized in topical sections: Part I (LNCS 8887) comprises computational bioimaging, computer graphics; motion, tracking, feature extraction and matching, segmentation, visualization, mapping, modeling and surface reconstruction, unmanned autonomous systems, medical imaging, tracking for human activity monitoring, intelligent transportation systems, visual perception and robotic systems. Part II (LNCS 8888) comprises topics such as computational bioimaging , recognition, computer vision, applications, face processing and recognition, virtual reality, and the poster sessions.
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Mathematical Methods for Signal and Image Analysis and Representation

Author: Luc Florack,Remco Duits,Geurt Jongbloed,Marie Colette van Lieshout,Laurie Davies

Publisher: Springer Science & Business Media

ISBN: 1447123522

Category: Mathematics

Page: 320

View: 4501

Mathematical Methods for Signal and Image Analysis and Representation presents the mathematical methodology for generic image analysis tasks. In the context of this book an image may be any m-dimensional empirical signal living on an n-dimensional smooth manifold (typically, but not necessarily, a subset of spacetime). The existing literature on image methodology is rather scattered and often limited to either a deterministic or a statistical point of view. In contrast, this book brings together these seemingly different points of view in order to stress their conceptual relations and formal analogies. Furthermore, it does not focus on specific applications, although some are detailed for the sake of illustration, but on the methodological frameworks on which such applications are built, making it an ideal companion for those seeking a rigorous methodological basis for specific algorithms as well as for those interested in the fundamental methodology per se. Covering many topics at the forefront of current research, including anisotropic diffusion filtering of tensor fields, this book will be of particular interest to graduate and postgraduate students and researchers in the fields of computer vision, medical imaging and visual perception.
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Geometry, Morphology, and Computational Imaging

11th International Workshop on Theoretical Foundations of Computer Vision, Dagstuhl Castle, Germany, April 7-12, 2002, Revised Papers

Author: Tetsuo Asano,Reinhard Klette,International Workshop on Theoretical Foundations of Computer Vision

Publisher: Springer Science & Business Media

ISBN: 3540009167

Category: Computers

Page: 436

View: 9024

This book constitutes the thoroughly refereed post-proceedings of the 11th International Workshop on Theoretical Foundations of Computer Vision, held in Dagstuhl Castle, Germany in April 2002. The 27 revised full papers presented went through two rounds of reviewing and improvement and assess the state of the art in geometry, morphology, and computational imaging. The papers are organized in sections on geometry - models and algorithms; property measurement in the grid and on finite samples; features, shape, and morphology; and computer vision and scene analysis.
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Image Processing and Analysis with Graphs

Theory and Practice

Author: Olivier Lezoray,Leo Grady

Publisher: CRC Press

ISBN: 1351833170

Category: Computers

Page: 570

View: 761

Covering the theoretical aspects of image processing and analysis through the use of graphs in the representation and analysis of objects, Image Processing and Analysis with Graphs: Theory and Practice also demonstrates how these concepts are indispensible for the design of cutting-edge solutions for real-world applications. Explores new applications in computational photography, image and video processing, computer graphics, recognition, medical and biomedical imaging With the explosive growth in image production, in everything from digital photographs to medical scans, there has been a drastic increase in the number of applications based on digital images. This book explores how graphs—which are suitable to represent any discrete data by modeling neighborhood relationships—have emerged as the perfect unified tool to represent, process, and analyze images. It also explains why graphs are ideal for defining graph-theoretical algorithms that enable the processing of functions, making it possible to draw on the rich literature of combinatorial optimization to produce highly efficient solutions. Some key subjects covered in the book include: Definition of graph-theoretical algorithms that enable denoising and image enhancement Energy minimization and modeling of pixel-labeling problems with graph cuts and Markov Random Fields Image processing with graphs: targeted segmentation, partial differential equations, mathematical morphology, and wavelets Analysis of the similarity between objects with graph matching Adaptation and use of graph-theoretical algorithms for specific imaging applications in computational photography, computer vision, and medical and biomedical imaging Use of graphs has become very influential in computer science and has led to many applications in denoising, enhancement, restoration, and object extraction. Accounting for the wide variety of problems being solved with graphs in image processing and computer vision, this book is a contributed volume of chapters written by renowned experts who address specific techniques or applications. This state-of-the-art overview provides application examples that illustrate practical application of theoretical algorithms. Useful as a support for graduate courses in image processing and computer vision, it is also perfect as a reference for practicing engineers working on development and implementation of image processing and analysis algorithms.
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Mathematical Morphology and its Applications to Image and Signal Processing

Author: Henk J.A.M. Heijmans,Jos Roerdink

Publisher: Springer Science & Business Media

ISBN: 9780792351337

Category: Mathematics

Page: 442

View: 5971

This book contains the proceedings of the International Symposium on Mathematical Morphology and its Applications to Image and Signal Processing IV, held June 3-5, 1998, in Amsterdam, The Netherlands. The purpose of the work is to provide the image analysis community with a sampling of recent developments in theoretical and practical aspects of mathematical morphology and its applications to image and signal processing. Among the areas covered are: digitization and connectivity, skeletonization, multivariate morphology, morphological segmentation, color image processing, filter design, gray-scale morphology, fuzzy morphology, decomposition of morphological operators, random sets and statistical inference, differential morphology and scale-space, morphological algorithms and applications. Audience: This volume will be of interest to research mathematicians and computer scientists whose work involves mathematical morphology, image and signal processing.
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Mathematical Morphology and Its Applications to Image and Signal Processing

Author: Petros Maragos,Ronald W. Schafer,Muhammad Akmal Butt

Publisher: Springer Science & Business Media

ISBN: 9780792397335

Category: Computers

Page: 476

View: 8241

Mathematical morphology (MM) is a powerful methodology for the quantitative analysis of geometrical structures. It consists of a broad and coherent collection of theoretical concepts, nonlinear signal operators, and algorithms aiming at extracting, from images or other geometrical objects, information related to their shape and size. Its mathematical origins stem from set theory, lattice algebra, and integral and stochastic geometry. MM was initiated in the late 1960s by G. Matheron and J. Serra at the Fontainebleau School of Mines in France. Originally it was applied to analyzing images from geological or biological specimens. However, its rich theoretical framework, algorithmic efficiency, easy implementability on special hardware, and suitability for many shape- oriented problems have propelled its widespread diffusion and adoption by many academic and industry groups in many countries as one among the dominant image analysis methodologies. The purpose of Mathematical Morphology and its Applications to Image and Signal Processing is to provide the image analysis community with a sampling from the current developments in the theoretical (deterministic and stochastic) and computational aspects of MM and its applications to image and signal processing. The book consists of the papers presented at the ISMM'96 grouped into the following themes: Theory Connectivity Filtering Nonlinear System Related to Morphology Algorithms/Architectures Granulometries, Texture Segmentation Image Sequence Analysis Learning Document Analysis Applications
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Mathematical Morphology and Its Applications to Image Processing

Author: Jean Serra,Pierre Soille

Publisher: Springer Science & Business Media

ISBN: 9401110409

Category: Computers

Page: 385

View: 4816

Mathematical morphology (MM) is a theory for the analysis of spatial structures. It is called morphology since it aims at analysing the shape and form of objects, and it is mathematical in the sense that the analysis is based on set theory, topology, lattice algebra, random functions, etc. MM is not only a theory, but also a powerful image analysis technique. The purpose of the present book is to provide the image analysis community with a snapshot of current theoretical and applied developments of MM. The book consists of forty-five contributions classified by subject. It demonstrates a wide range of topics suited to the morphological approach.
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Medical Imaging 2004

16-19 February 2004, San Diego, California, USA. Image processing

Author: N.A

Publisher: N.A

ISBN: N.A

Category: Diagnostic imaging

Page: 2158

View: 2288

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Energy Minimization Methods in Computer Vision and Pattern Recognition

5th International Workshop, EMMCVPR 2005, St. Augustine, FL, USA, November 9-11, 2005, Proceedings

Author: Anand Rangarajan,Baba Vemuri

Publisher: Springer Science & Business Media

ISBN: 3540302875

Category: Computers

Page: 666

View: 8631

This volume consists of the 42 papers presented at the International Workshop on Energy Minimization Methods in Computer Vision and Pattern Recog- tion (EMMCVPR 2005), which was held at the Hilton St. Augustine Historic Bayfront, St. Augustine, Florida, USA, during November9 11,2005.This wo- shop is the ?fth in a series which began with EMMCVPR 1997 held in Venice, Italy, in May 1997 and continued with EMMCVPR 1999 held in York, UK, in July 1999, EMMCVPR 2001 held in Sophia-Antipolis, France, in September 2001 and EMMCVPR 2003 held in Lisbon, Portugal, in July 2003. Many problems in computer vision and pattern recognition (CVPR) are couchedintheframeworkofoptimization.Theminimizationofaglobalquantity, often referred to as the energy, forms the bulwark of most approachesin CVPR. Disparate approaches such as discrete and probabilistic formulations on the one hand and continuous, deterministic strategies on the other often have optimi- tion or energy minimization as a common theme. Instances of energy minimi- tion arise in Gibbs/Markov modeling, Bayesian decision theory, geometric and variational approaches and in areas in CVPR such as object recognition and - trieval, image segmentation, registration, reconstruction, classi?cation and data mining. The aim of this workshop was to bring together researchers with interests in thesedisparateareasofCVPRbutwithanunderlyingcommitmenttosomeform of not only energy minimization but global optimization in general. Although thesubjectistraditionallywellrepresentedinmajorinternationalconferenceson CVPR, recent advances information geometry, Bayesian networks and gra- ical models, Markov chain Monte Carlo, graph algorithms, implicit methods in variational approaches and PDEs deserve an informal and focused hearing in a workshop setting."
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Medical imaging 2006

Author: J. Michael Fitzpatrick,Joseph M. Reinhardt,Josien P. W. Pluim,Milan Sonka,American Association of Physicists in Medicine

Publisher: Society of Photo Optical

ISBN: 9780819452832

Category: Imaging systems in medicine

Page: 2158

View: 9681

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Shape Analysis in Medical Image Analysis

Author: Shuo Li,João Manuel R. S. Tavares

Publisher: Springer Science & Business Media

ISBN: 3319038133

Category: Technology & Engineering

Page: 442

View: 752

This book contains thirteen contributions from invited experts of international recognition addressing important issues in shape analysis in medical image analysis, including techniques for image segmentation, registration, modelling and classification and applications in biology, as well as in cardiac, brain, spine, chest, lung and clinical practice. This volume treats topics such as for example, anatomic and functional shape representation and matching; shape-based medical image segmentation; shape registration; statistical shape analysis; shape deformation; shape-based abnormity detection; shape tracking and longitudinal shape analysis; machine learning for shape modeling and analysis; shape-based computer-aided-diagnosis; shape-based medical navigation; benchmark and validation of shape representation, analysis and modeling algorithms. This work will be of interest to researchers, students and manufacturers in the fields of artificial intelligence, bioengineering, biomechanics, computational mechanics, computational vision, computer sciences, human motion, mathematics, medical imaging, medicine, pattern recognition and physics.
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Emerging Trends in Image Processing, Computer Vision and Pattern Recognition

Author: Leonidas Deligiannidis,Hamid R Arabnia

Publisher: Morgan Kaufmann

ISBN: 012802092X

Category: Computers

Page: 640

View: 3400

Emerging Trends in Image Processing, Computer Vision, and Pattern Recognition discusses the latest in trends in imaging science which at its core consists of three intertwined computer science fields, namely: Image Processing, Computer Vision, and Pattern Recognition. There is significant renewed interest in each of these three fields fueled by Big Data and Data Analytic initiatives including but not limited to; applications as diverse as computational biology, biometrics, biomedical imaging, robotics, security, and knowledge engineering. These three core topics discussed here provide a solid introduction to image processing along with low-level processing techniques, computer vision fundamentals along with examples of applied applications and pattern recognition algorithms and methodologies that will be of value to the image processing and computer vision research communities. Drawing upon the knowledge of recognized experts with years of practical experience and discussing new and novel applications Editors’ Leonidas Deligiannidis and Hamid Arabnia cover; Many perspectives of image processing spanning from fundamental mathematical theory and sampling, to image representation and reconstruction, filtering in spatial and frequency domain, geometrical transformations, and image restoration and segmentation Key application techniques in computer vision some of which are camera networks and vision, image feature extraction, face and gesture recognition and biometric authentication Pattern recognition algorithms including but not limited to; Supervised and unsupervised classification algorithms, Ensemble learning algorithms, and parsing algorithms. How to use image processing and visualization to analyze big data. Discusses novel applications that can benefit from image processing, computer vision and pattern recognition such as computational biology, biometrics, biomedical imaging, robotics, security, and knowledge engineering. Covers key application techniques in computer vision from fundamentals to mid to high level processing some of which are camera networks and vision, image feature extraction, face and gesture recognition and biometric authentication. Presents a number of pattern recognition algorithms and methodologies including but not limited to; supervised and unsupervised classification algorithms, Ensemble learning algorithms, and parsing algorithms. Explains how to use image processing and visualization to analyze big data.
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Computational Texture and Patterns

From Textons to Deep Learning

Author: Kristin J. Dana

Publisher: Morgan & Claypool Publishers

ISBN: 168173012X

Category: Computers

Page: 113

View: 6176

Visual pattern analysis is a fundamental tool in mining data for knowledge. Computational representations for patterns and texture allow us to summarize, store, compare, and label in order to learn about the physical world. Our ability to capture visual imagery with cameras and sensors has resulted in vast amounts of raw data, but using this information effectively in a task-specific manner requires sophisticated computational representations. We enumerate specific desirable traits for these representations: (1) intraclass invariance—to support recognition; (2) illumination and geometric invariance for robustness to imaging conditions; (3) support for prediction and synthesis to use the model to infer continuation of the pattern; (4) support for change detection to detect anomalies and perturbations; and (5) support for physics-based interpretation to infer system properties from appearance. In recent years, computer vision has undergone a metamorphosis with classic algorithms adapting to new trends in deep learning. This text provides a tour of algorithm evolution including pattern recognition, segmentation and synthesis. We consider the general relevance and prominence of visual pattern analysis and applications that rely on computational models.
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Topological Methods in Data Analysis and Visualization III

Theory, Algorithms, and Applications

Author: Peer-Timo Bremer,Ingrid Hotz,Valerio Pascucci,Ronald Peikert

Publisher: Springer Science & Business

ISBN: 3319040995

Category: Mathematics

Page: 279

View: 7860

This collection of peer-reviewed conference papers provides comprehensive coverage of cutting-edge research in topological approaches to data analysis and visualization. It encompasses the full range of new algorithms and insights, including fast homology computation, comparative analysis of simplification techniques, and key applications in materials and medical science. The volume also features material on core research challenges such as the representation of large and complex datasets and integrating numerical methods with robust combinatorial algorithms. Reflecting the focus of the TopoInVis 2013 conference, the contributions evince the progress currently being made on finding experimental solutions to open problems in the sector. They provide an inclusive snapshot of state-of-the-art research that enables researchers to keep abreast of the latest developments and provides a foundation for future progress. With papers by some of the world’s leading experts in topological techniques, this volume is a major contribution to the literature in a field of growing importance with applications in disciplines that range from engineering to medicine.
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Geometric Level Set Methods in Imaging, Vision, and Graphics

Author: Stanley Osher,Nikos Paragios

Publisher: Springer Science & Business Media

ISBN: 0387954880

Category: Computers

Page: 513

View: 7675

Here is, for the first time, a book that clearly explains and applies new level set methods to problems and applications in computer vision, graphics, and imaging. It is an essential compilation of survey chapters from the leading researchers in the field. The applications of the methods are emphasized.
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Applied Graph Theory in Computer Vision and Pattern Recognition

Author: Abraham Kandel,Horst Bunke,Mark Last

Publisher: Springer Science & Business Media

ISBN: 3540680195

Category: Computers

Page: 265

View: 2186

This book will serve as a foundation for a variety of useful applications of graph theory to computer vision, pattern recognition, and related areas. It covers a representative set of novel graph-theoretic methods for complex computer vision and pattern recognition tasks. The first part of the book presents the application of graph theory to low-level processing of digital images such as a new method for partitioning a given image into a hierarchy of homogeneous areas using graph pyramids, or a study of the relationship between graph theory and digital topology. Part II presents graph-theoretic learning algorithms for high-level computer vision and pattern recognition applications, including a survey of graph based methodologies for pattern recognition and computer vision, a presentation of a series of computationally efficient algorithms for testing graph isomorphism and related graph matching tasks in pattern recognition and a new graph distance measure to be used for solving graph matching problems. Finally, Part III provides detailed descriptions of several applications of graph-based methods to real-world pattern recognition tasks. It includes a critical review of the main graph-based and structural methods for fingerprint classification, a new method to visualize time series of graphs, and potential applications in computer network monitoring and abnormal event detection.
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Computational Noncommutative Algebra and Applications

Proceedings of the NATO Advanced Study Institute, on Computatoinal Noncommutative Algebra and Applications, Il Ciocco, Italy, 6-19 July 2003

Author: Jim Byrnes,Gerald Ostheimer

Publisher: Springer Science & Business Media

ISBN: 1402023073

Category: Mathematics

Page: 428

View: 9789

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