Image Segmentation Using Combinatorial Optimization Algorithms PDF Download
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Author: Hui Zhang
Publisher:
ISBN:
Category :
Languages : en
Pages : 144
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Book Description
Author: Hui Zhang
Publisher:
ISBN:
Category :
Languages : en
Pages : 144
Get Book Here
Book Description
Author: Reneta P. Barneva
Publisher: Springer Science & Business Media
ISBN: 3540782745
Category : Computers
Languages : en
Pages : 459
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Book Description
This volume constitutes the refereed proceedings of the 12th International Workshop on Combinatorial Image Analysis, IWCIA 2008, held in Buffalo, NY, USA, in April 2008. The 28 revised full papers and 10 revised poster papers presented were carefully reviewed and selected from 117 initial submissions. The papers are organized in topical sections on digital geometry and topology, curves and surfaces, combinatorics in digital spaces: lattice polygons, polytopes, tilings, and patterns, image representation, segmentation, grouping, and reconstruction, applications of computational geometry, integer and linear programming to image analysis, fuzzy and stochastic image analysis, parallel architectures and algorithms, grammars and models for image or scene analysis, as well as discrete tomography, medical imaging, and biometrics.
Author: Frank Neumann
Publisher: Springer Science & Business Media
ISBN: 3642165443
Category : Mathematics
Languages : en
Pages : 215
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Book Description
Bioinspired computation methods such as evolutionary algorithms and ant colony optimization are being applied successfully to complex engineering problems and to problems from combinatorial optimization, and with this comes the requirement to more fully understand the computational complexity of these search heuristics. This is the first textbook covering the most important results achieved in this area. The authors study the computational complexity of bioinspired computation and show how runtime behavior can be analyzed in a rigorous way using some of the best-known combinatorial optimization problems -- minimum spanning trees, shortest paths, maximum matching, covering and scheduling problems. A feature of the book is the separate treatment of single- and multiobjective problems, the latter a domain where the development of the underlying theory seems to be lagging practical successes. This book will be very valuable for teaching courses on bioinspired computation and combinatorial optimization. Researchers will also benefit as the presentation of the theory covers the most important developments in the field over the last 10 years. Finally, with a focus on well-studied combinatorial optimization problems rather than toy problems, the book will also be very valuable for practitioners in this field.
Author: Sandip Dey
Publisher: John Wiley & Sons
ISBN: 1119488753
Category : Technology & Engineering
Languages : en
Pages : 374
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Book Description
Introduces quantum inspired techniques for image analysis for pure and true gray scale/color images in a single/multi-objective environment This book will entice readers to design efficient meta-heuristics for image analysis in the quantum domain. It introduces them to the essence of quantum computing paradigm, its features, and properties, and elaborates on the fundamentals of different meta-heuristics and their application to image analysis. As a result, it will pave the way for designing and developing quantum computing inspired meta-heuristics to be applied to image analysis. Quantum Inspired Meta-heuristics for Image Analysis begins with a brief summary on image segmentation, quantum computing, and optimization. It also highlights a few relevant applications of the quantum based computing algorithms, meta-heuristics approach, and several thresholding algorithms in vogue. Next, it discusses a review of image analysis before moving on to an overview of six popular meta-heuristics and their algorithms and pseudo-codes. Subsequent chapters look at quantum inspired meta-heuristics for bi-level and gray scale multi-level image thresholding; quantum behaved meta-heuristics for true color multi-level image thresholding; and quantum inspired multi-objective algorithms for gray scale multi-level image thresholding. Each chapter concludes with a summary and sample questions. Provides in-depth analysis of quantum mechanical principles Offers comprehensive review of image analysis Analyzes different state-of-the-art image thresholding approaches Detailed current, popular standard meta-heuristics in use today Guides readers step by step in the build-up of quantum inspired meta-heuristics Includes a plethora of real life case studies and applications Features statistical test analysis of the performances of the quantum inspired meta-heuristics vis-à-vis their conventional counterparts Quantum Inspired Meta-heuristics for Image Analysis is an excellent source of information for anyone working with or learning quantum inspired meta-heuristics for image analysis.
Author: Mehdi Toloo
Publisher: Academic Press
ISBN: 0128238003
Category : Science
Languages : en
Pages : 316
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Book Description
Multi-Objective Combinatorial Optimization Problems and Solution Methods discusses the results of a recent multi-objective combinatorial optimization achievement that considered metaheuristic, mathematical programming, heuristic, hyper heuristic and hybrid approaches. In other words, the book presents various multi-objective combinatorial optimization issues that may benefit from different methods in theory and practice. Combinatorial optimization problems appear in a wide range of applications in operations research, engineering, biological sciences and computer science, hence many optimization approaches have been developed that link the discrete universe to the continuous universe through geometric, analytic and algebraic techniques. This book covers this important topic as computational optimization has become increasingly popular as design optimization and its applications in engineering and industry have become ever more important due to more stringent design requirements in modern engineering practice. Presents a collection of the most up-to-date research, providing a complete overview of multi-objective combinatorial optimization problems and applications Introduces new approaches to handle different engineering and science problems, providing the field with a collection of related research not already covered in the primary literature Demonstrates the efficiency and power of the various algorithms, problems and solutions, including numerous examples that illustrate concepts and algorithms
Author: Pei-Gee Ho
Publisher: BoD – Books on Demand
ISBN: 9533072288
Category : Computers
Languages : en
Pages : 554
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Book Description
It was estimated that 80% of the information received by human is visual. Image processing is evolving fast and continually. During the past 10 years, there has been a significant research increase in image segmentation. To study a specific object in an image, its boundary can be highlighted by an image segmentation procedure. The objective of the image segmentation is to simplify the representation of pictures into meaningful information by partitioning into image regions. Image segmentation is a technique to locate certain objects or boundaries within an image. There are many algorithms and techniques have been developed to solve image segmentation problems, the research topics in this book such as level set, active contour, AR time series image modeling, Support Vector Machines, Pixon based image segmentations, region similarity metric based technique, statistical ANN and JSEG algorithm were written in details. This book brings together many different aspects of the current research on several fields associated to digital image segmentation. Four parts allowed gathering the 27 chapters around the following topics: Survey of Image Segmentation Algorithms, Image Segmentation methods, Image Segmentation Applications and Hardware Implementation. The readers will find the contents in this book enjoyable and get many helpful ideas and overviews on their own study.
Author: Ritu Arora
Publisher: CRC Press
ISBN: 1000859819
Category : Business & Economics
Languages : en
Pages : 221
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Book Description
This book discusses the basic ideas, underlying principles, mathematical formulations, analysis and applications of the different combinatorial problems under uncertainty and attempts to provide solutions for the same. Uncertainty influences the behaviour of the market to a great extent. Global pandemics and calamities are other factors which affect and augment unpredictability in the market. The intent of this book is to develop mathematical structures for different aspects of allocation problems depicting real life scenarios. The novel methods which are incorporated in practical scenarios under uncertain circumstances include the STAR heuristic approach, Matrix geometric method, Ranking function and Pythagorean fuzzy numbers, to name a few. Distinct problems which are considered in this book under uncertainty include scheduling, cyclic bottleneck assignment problem, bilevel transportation problem, multi-index transportation problem, retrial queuing, uncertain matrix games, optimal production evaluation of cotton in different soil and water conditions, the healthcare sector, intuitionistic fuzzy quadratic programming problem, and multi-objective optimization problem. This book may serve as a valuable reference for researchers working in the domain of optimization for solving combinatorial problems under uncertainty. The contributions of this book may further help to explore new avenues leading toward multidisciplinary research discussions.
Author: Petra Wiederhold
Publisher: Springer Science & Business Media
ISBN: 3642102085
Category : Computers
Languages : en
Pages : 450
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Book Description
The articles included in this volume were presented at the 13th International Workshop on Combinatorial Image Analysis, IWCIA 2009, held at Playa del Carmen, Yucatan Peninsula, Mexico, November 24-27, 2009. The 12 previous meetings were held in Paris (France) 1991, Ube (Japan) 1992, Washington DC (USA) 1994,Lyon(France) 1995,Hiroshima(Japan) 1997,Madras(India) 1999, Caen (France) 2000, Philadelphia (USA) 2001, Palermo (Italy) 2003, Auckland (New Zealand) 2004, Berlin (Germany) 2006, and Bu?alo (USA) 2008. Imageanalysisisa scienti?c discipline whichprovidestheoreticalfoundations and methods for solving problems appearing in a range of areas as diverse as biology,medicine,physics,astronomy,geography,chemistry,robotics,andind- trial manufacturing. It deals with algorithms and methods aimed at extracting meaningful information from images. The processing is done through computer systems, and the focus is, therefore, on images presented in digital form. Unlike traditional approaches, which are based on continuous models requiring ?oat arithmetic computations and rounding, “combinatorial” approaches to image analysis (also named “discrete” or “digital” approaches) are based on studying the combinatorial properties of the digital images. They provide models and - gorithms, which are generally more e?cient and accurate than those based on continuous models. Some recent combinatorial approaches aim at constructing self-contained digital topology and geometry, which might be of interest and - portancenot only for imageanalysis,but also asa distinct theoretical discipline. Following the call for papers, IWCIA 2009 received 70 submissions. After a rigorous review process, 32 were accepted for inclusion in this volume.
Author: Meera Ramadas
Publisher: Springer
ISBN: 3030040976
Category : Technology & Engineering
Languages : en
Pages : 163
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Book Description
In this book, differential evolution and its modified variants are applied to the clustering of data and images. Metaheuristics have emerged as potential algorithms for dealing with complex optimization problems, which are otherwise difficult to solve using traditional methods. In this regard, differential evolution is considered to be a highly promising technique for optimization and is being used to solve various real-time problems. The book studies the algorithms in detail, tests them on a range of test images, and carefully analyzes their performance. Accordingly, it offers a valuable reference guide for all researchers, students and practitioners working in the fields of artificial intelligence, optimization and data analytics.
Author: Jean-Michel Morel
Publisher: Springer Science & Business Media
ISBN: 1468405675
Category : Mathematics
Languages : en
Pages : 257
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Book Description
This book contains both a synthesis and mathematical analysis of a wide set of algorithms and theories whose aim is the automatic segmen tation of digital images as well as the understanding of visual perception. A common formalism for these theories and algorithms is obtained in a variational form. Thank to this formalization, mathematical questions about the soundness of algorithms can be raised and answered. Perception theory has to deal with the complex interaction between regions and "edges" (or boundaries) in an image: in the variational seg mentation energies, "edge" terms compete with "region" terms in a way which is supposed to impose regularity on both regions and boundaries. This fact was an experimental guess in perception phenomenology and computer vision until it was proposed as a mathematical conjecture by Mumford and Shah. The third part of the book presents a unified presentation of the evi dences in favour of the conjecture. It is proved that the competition of one-dimensional and two-dimensional energy terms in a variational for mulation cannot create fractal-like behaviour for the edges. The proof of regularity for the edges of a segmentation constantly involves con cepts from geometric measure theory, which proves to be central in im age processing theory. The second part of the book provides a fast and self-contained presentation of the classical theory of rectifiable sets (the "edges") and unrectifiable sets ("fractals").
