Modern Metaheuristics In Image Processing

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Modern Metaheuristics in Image Processing

Author : Diego Oliva
Publisher : CRC Press
ISBN 13 : 1000800202
Total Pages : 140 pages
Book Rating : 4.0/5 (8 download)

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Book Synopsis Modern Metaheuristics in Image Processing by : Diego Oliva

Download or read book Modern Metaheuristics in Image Processing written by Diego Oliva and published by CRC Press. This book was released on 2022-09-28 with total page 140 pages. Available in PDF, EPUB and Kindle. Book excerpt: The use of metaheuristic algorithms (MA) has been increasing in recent years, and the image processing field is not the exempted of their application. In the last two years a big amount of MA has been introduced as alternatives for solving complex optimization problems. This book collects the most prominent MA of the 2019 and 2020 and verifies its use in image processing tasks. In addition, literature review of both MA and digital image processing is presented as part of the introductory information. Each algorithm is detailed explained with special focus in the tuning parameters and the proper implementation for the image processing tasks. Besides several examples permits to the reader explore and confirm the use of this kind of intelligent methods. Since image processing is widely used in different domains, this book considers different kinds of datasets that includes, magnetic resonance images, thermal images, agriculture images, among others. The reader then can have some ideas of implementation that complement the theory exposed of each optimization mechanism. Regarding the image processing problems this book consider the segmentation by using different metrics based on entropies or variances. In the same way, the identification of different shapes and the detection of objects are also covered in the corresponding chapters. Each chapter is complemented with a wide range of experiments and statistical analysis that permits the reader to judge about the performance of the MA. Finally, there is included a section that includes some discussion and conclusions. This section also provides some open questions and research opportunities for the audience.

Applications of Hybrid Metaheuristic Algorithms for Image Processing

Author : Diego Oliva
Publisher : Springer Nature
ISBN 13 : 3030409775
Total Pages : 488 pages
Book Rating : 4.0/5 (34 download)

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Book Synopsis Applications of Hybrid Metaheuristic Algorithms for Image Processing by : Diego Oliva

Download or read book Applications of Hybrid Metaheuristic Algorithms for Image Processing written by Diego Oliva and published by Springer Nature. This book was released on 2020-03-27 with total page 488 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents a collection of the most recent hybrid methods for image processing. The algorithms included consider evolutionary, swarm, machine learning and deep learning. The respective chapters explore different areas of image processing, from image segmentation to the recognition of objects using complex approaches and medical applications. The book also discusses the theory of the methodologies used to provide an overview of the applications of these tools in image processing. The book is primarily intended for undergraduate and postgraduate students of science, engineering and computational mathematics, and can also be used for courses on artificial intelligence, advanced image processing, and computational intelligence. Further, it is a valuable resource for researchers from the evolutionary computation, artificial intelligence and image processing communities.

Engineering Applications of Modern Metaheuristics

Author : Taymaz Akan
Publisher : Springer Nature
ISBN 13 : 3031168321
Total Pages : 209 pages
Book Rating : 4.0/5 (311 download)

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Book Synopsis Engineering Applications of Modern Metaheuristics by : Taymaz Akan

Download or read book Engineering Applications of Modern Metaheuristics written by Taymaz Akan and published by Springer Nature. This book was released on 2022-12-04 with total page 209 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is a collection of various methodologies that make it possible for metaheuristics and hyper-heuristics to solve problems that occur in the real world. This book contains chapters that make use of metaheuristics techniques. The application fields range from image processing to transmission power control, and case studies and literature reviews are included to assist the reader. Furthermore, some chapters present cutting-edge methods for load frequency control and IoT implementations. In this sense, the book offers both theoretical and practical contents in the form of metaheuristic algorithms. The researchers used several stochastic optimization methods in this book, including evolutionary algorithms and Swarm-based algorithms. The chapters were written from a scientific standpoint. As a result, the book is primarily aimed at undergraduate and postgraduate students of Science, Engineering, and Computational Mathematics, but it can also be used in courses on Artificial Intelligence, among other things. Similarly, the material may be beneficial to research in evolutionary computation and artificial intelligence communities.

Metaheuristic Algorithms for Image Segmentation: Theory and Applications

Author : Diego Oliva
Publisher : Springer
ISBN 13 : 3030129314
Total Pages : 226 pages
Book Rating : 4.0/5 (31 download)

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Book Synopsis Metaheuristic Algorithms for Image Segmentation: Theory and Applications by : Diego Oliva

Download or read book Metaheuristic Algorithms for Image Segmentation: Theory and Applications written by Diego Oliva and published by Springer. This book was released on 2019-03-02 with total page 226 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents a study of the most important methods of image segmentation and how they are extended and improved using metaheuristic algorithms. The segmentation approaches selected have been extensively applied to the task of segmentation (especially in thresholding), and have also been implemented using various metaheuristics and hybridization techniques leading to a broader understanding of how image segmentation problems can be solved from an optimization perspective. The field of image processing is constantly changing due to the extensive integration of cameras in devices; for example, smart phones and cars now have embedded cameras. The images have to be accurately analyzed, and crucial pre-processing steps, like image segmentation, and artificial intelligence, including metaheuristics, are applied in the automatic analysis of digital images. Metaheuristic algorithms have also been used in various fields of science and technology as the demand for new methods designed to solve complex optimization problems increases. This didactic book is primarily intended for undergraduate and postgraduate students of science, engineering, and computational mathematics. It is also suitable for courses such as artificial intelligence, advanced image processing, and computational intelligence. The material is also useful for researches in the fields of evolutionary computation, artificial intelligence, and image processing.

Hybrid Metaheuristics for Image Analysis

Author : Siddhartha Bhattacharyya
Publisher : Springer
ISBN 13 : 3319776258
Total Pages : 263 pages
Book Rating : 4.3/5 (197 download)

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Book Synopsis Hybrid Metaheuristics for Image Analysis by : Siddhartha Bhattacharyya

Download or read book Hybrid Metaheuristics for Image Analysis written by Siddhartha Bhattacharyya and published by Springer. This book was released on 2018-07-30 with total page 263 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents contributions in the field of computational intelligence for the purpose of image analysis. The chapters discuss how problems such as image segmentation, edge detection, face recognition, feature extraction, and image contrast enhancement can be solved using techniques such as genetic algorithms and particle swarm optimization. The contributions provide a multidimensional approach, and the book will be useful for researchers in computer science, electrical engineering, and information technology.

Quantum Inspired Meta-heuristics for Image Analysis

Author : Sandip Dey
Publisher : John Wiley & Sons
ISBN 13 : 111948877X
Total Pages : 6 pages
Book Rating : 4.1/5 (194 download)

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Book Synopsis Quantum Inspired Meta-heuristics for Image Analysis by : Sandip Dey

Download or read book Quantum Inspired Meta-heuristics for Image Analysis written by Sandip Dey and published by John Wiley & Sons. This book was released on 2019-05-29 with total page 6 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Image Segmentation Through Metaheuristics Optimization

Author : Thuy Xuan Pham
Publisher :
ISBN 13 :
Total Pages : 0 pages
Book Rating : 4.:/5 (129 download)

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Book Synopsis Image Segmentation Through Metaheuristics Optimization by : Thuy Xuan Pham

Download or read book Image Segmentation Through Metaheuristics Optimization written by Thuy Xuan Pham and published by . This book was released on 2019 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Image segmentation is the process of partitioning an image into smaller non-overlapped and meaningful regions based in part on some homogeneity characteristics. Many high-level processing tasks such as feature extraction, object recognition and medical diagnosis depend heavily on the quality of solutions. In medical image analysis, images usually contain some artifacts such as noise, image volume effect and bias field effect due to various factors, for instance, environment and acquisition devices, and have complex structures. Therefore, image segmentation remains a difficult task even if various techniques and methods of different accuracy and degree of complexity have been introduced in the literature. Several approaches such as fuzzy clustering, region-based active contour, Markov random field, have been found that can produce promising results; however, still many key open issues remain to be investigated. Up to now, there is no gold standard method and segmentation procedures still need a significant amount of expert intervention for improving the performance.Metaheuristics are a high-level procedure designed to solve optimization problems by the process of searching optimal solutions to a particular problem of interest. Metaheuristics are generally applied to problems for which there is no satisfactory algorithm able to solve them effectively. Therefore, they are widely used to solve complex problems and have proven to be successful in many fields of application with varying degrees of success. Considering the image segmentation problem as one of the optimization problems solved by metaheuristics, image segmentation has attracted many researchers in recent years. In many successful applications, it can be seen that the traditional approaches for image segmentation have been combined with metaheuristics in different perspectives in order to improve their performance.Bearing those in mind, we propose in this work three image segmentation methods for magnetic resonance (MR) brain images based on mono-objective, multi-objective and hybrid metaheuristic optimization techniques. In each method, first, the basic model for the image segmentation problem is extended to incorporate more image information (spatial or spectral) such that more and better characteristics in segmented image can be achieved. Then, metaheuristic algorithms are adapted or developed to take place in optimization step. The proposed methods were evaluated on both simulated MR images and real MR images and compared with a set of recent methods in the literature. The obtained results show clearly the efficiency of the proposed ideas.Keywords: Image segmentation, fuzzy clustering, region-based active contour, Markov random field, metaheuristics, multi-objective optimization, hybrid metaheuristic, MRI.

Metaheuristic Algorithms in Industry 4.0

Author : Pritesh Shah
Publisher : CRC Press
ISBN 13 : 1000435989
Total Pages : 302 pages
Book Rating : 4.0/5 (4 download)

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Book Synopsis Metaheuristic Algorithms in Industry 4.0 by : Pritesh Shah

Download or read book Metaheuristic Algorithms in Industry 4.0 written by Pritesh Shah and published by CRC Press. This book was released on 2021-09-29 with total page 302 pages. Available in PDF, EPUB and Kindle. Book excerpt: Due to increasing industry 4.0 practices, massive industrial process data is now available for researchers for modelling and optimization. Artificial Intelligence methods can be applied to the ever-increasing process data to achieve robust control against foreseen and unforeseen system fluctuations. Smart computing techniques, machine learning, deep learning, computer vision, for example, will be inseparable from the highly automated factories of tomorrow. Effective cybersecurity will be a must for all Internet of Things (IoT) enabled work and office spaces. This book addresses metaheuristics in all aspects of Industry 4.0. It covers metaheuristic applications in IoT, cyber physical systems, control systems, smart computing, artificial intelligence, sensor networks, robotics, cybersecurity, smart factory, predictive analytics and more. Key features: Includes industrial case studies. Includes chapters on cyber physical systems, machine learning, deep learning, cybersecurity, robotics, smart manufacturing and predictive analytics. surveys current trends and challenges in metaheuristics and industry 4.0. Metaheuristic Algorithms in Industry 4.0 provides a guiding light to engineers, researchers, students, faculty and other professionals engaged in exploring and implementing industry 4.0 solutions in various systems and processes.

OpenMP in a Modern World: From Multi-device Support to Meta Programming

Author : Michael Klemm
Publisher : Springer Nature
ISBN 13 : 3031159225
Total Pages : 178 pages
Book Rating : 4.0/5 (311 download)

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Book Synopsis OpenMP in a Modern World: From Multi-device Support to Meta Programming by : Michael Klemm

Download or read book OpenMP in a Modern World: From Multi-device Support to Meta Programming written by Michael Klemm and published by Springer Nature. This book was released on 2022-09-20 with total page 178 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the proceedings of the 18th International Workshop on OpenMP, IWOMP 2022, held in Chattanooga, TN, USA, in September 2022. The 11 full papers presented in this volume were carefully reviewed and selected for inclusion in this book from the 13 submissions. The papers are organized in topical sections named: OpenMP and multiple nodes; exploring new and recent OpenMP extensions; effectie use of advanced heterogeneous node architectures; OpenMP tool support; OpenMP and multiple translation units. Chapter "Improving Tool Support for Nested Parallel Regions with Introspection Consistency" is publshed Open Access and licensed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/).

Meta-Heuristics Optimization Algorithms in Engineering, Business, Economics, and Finance

Author : Vasant, Pandian M.
Publisher : IGI Global
ISBN 13 : 1466620870
Total Pages : 735 pages
Book Rating : 4.4/5 (666 download)

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Book Synopsis Meta-Heuristics Optimization Algorithms in Engineering, Business, Economics, and Finance by : Vasant, Pandian M.

Download or read book Meta-Heuristics Optimization Algorithms in Engineering, Business, Economics, and Finance written by Vasant, Pandian M. and published by IGI Global. This book was released on 2012-09-30 with total page 735 pages. Available in PDF, EPUB and Kindle. Book excerpt: Optimization techniques have developed into a significant area concerning industrial, economics, business, and financial systems. With the development of engineering and financial systems, modern optimization has played an important role in service-centered operations and as such has attracted more attention to this field. Meta-heuristic hybrid optimization is a newly development mathematical framework based optimization technique. Designed by logicians, engineers, analysts, and many more, this technique aims to study the complexity of algorithms and problems. Meta-Heuristics Optimization Algorithms in Engineering, Business, Economics, and Finance explores the emerging study of meta-heuristics optimization algorithms and methods and their role in innovated real world practical applications. This book is a collection of research on the areas of meta-heuristics optimization algorithms in engineering, business, economics, and finance and aims to be a comprehensive reference for decision makers, managers, engineers, researchers, scientists, financiers, and economists as well as industrialists.

Bio-Inspired Computation and Applications in Image Processing

Author : Xin-She Yang
Publisher : Academic Press
ISBN 13 : 012804537X
Total Pages : 376 pages
Book Rating : 4.1/5 (28 download)

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Book Synopsis Bio-Inspired Computation and Applications in Image Processing by : Xin-She Yang

Download or read book Bio-Inspired Computation and Applications in Image Processing written by Xin-She Yang and published by Academic Press. This book was released on 2016-08-09 with total page 376 pages. Available in PDF, EPUB and Kindle. Book excerpt: Bio-Inspired Computation and Applications in Image Processing summarizes the latest developments in bio-inspired computation in image processing, focusing on nature-inspired algorithms that are linked with deep learning, such as ant colony optimization, particle swarm optimization, and bat and firefly algorithms that have recently emerged in the field. In addition to documenting state-of-the-art developments, this book also discusses future research trends in bio-inspired computation, helping researchers establish new research avenues to pursue. - Reviews the latest developments in bio-inspired computation in image processing - Focuses on the introduction and analysis of the key bio-inspired methods and techniques - Combines theory with real-world applications in image processing - Helps solve complex problems in image and signal processing - Contains a diverse range of self-contained case studies in real-world applications

Recent Advances on Memetic Algorithms and its Applications in Image Processing

Author : D. Jude Hemanth
Publisher : Springer Nature
ISBN 13 : 9811513627
Total Pages : 209 pages
Book Rating : 4.8/5 (115 download)

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Book Synopsis Recent Advances on Memetic Algorithms and its Applications in Image Processing by : D. Jude Hemanth

Download or read book Recent Advances on Memetic Algorithms and its Applications in Image Processing written by D. Jude Hemanth and published by Springer Nature. This book was released on 2019-12-07 with total page 209 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book includes original research findings in the field of memetic algorithms for image processing applications. It gathers contributions on theory, case studies, and design methods pertaining to memetic algorithms for image processing applications ranging from defence, medical image processing, and surveillance, to computer vision, robotics, etc. The content presented here provides new directions for future research from both theoretical and practical viewpoints, and will spur further advances in the field.

Advancements in Applied Metaheuristic Computing

Author : Dey, Nilanjan
Publisher : IGI Global
ISBN 13 : 1522541527
Total Pages : 357 pages
Book Rating : 4.5/5 (225 download)

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Book Synopsis Advancements in Applied Metaheuristic Computing by : Dey, Nilanjan

Download or read book Advancements in Applied Metaheuristic Computing written by Dey, Nilanjan and published by IGI Global. This book was released on 2017-11-30 with total page 357 pages. Available in PDF, EPUB and Kindle. Book excerpt: Metaheuristic algorithms are present in various applications for different domains. Recently, researchers have conducted studies on the effectiveness of these algorithms in providing optimal solutions to complicated problems. Advancements in Applied Metaheuristic Computing is a crucial reference source for the latest empirical research on methods and approaches that include metaheuristics for further system improvements, and it offers outcomes of employing optimization algorithms. Featuring coverage on a broad range of topics such as manufacturing, genetic programming, and medical imaging, this publication is ideal for researchers, academicians, advanced-level students, and technology developers seeking current research on the use of optimization algorithms in several applications.

International Conference on Emerging Trends in Electrical, Communication and Information Technologies, Vol 1

Author :
Publisher : Elsevier - S&T Books
ISBN 13 : 8131234118
Total Pages : 366 pages
Book Rating : 4.1/5 (312 download)

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Book Synopsis International Conference on Emerging Trends in Electrical, Communication and Information Technologies, Vol 1 by :

Download or read book International Conference on Emerging Trends in Electrical, Communication and Information Technologies, Vol 1 written by and published by Elsevier - S&T Books. This book was released on with total page 366 pages. Available in PDF, EPUB and Kindle. Book excerpt:

VLSI and Hardware Implementations using Modern Machine Learning Methods

Author : Sandeep Saini
Publisher : CRC Press
ISBN 13 : 1000523845
Total Pages : 292 pages
Book Rating : 4.0/5 (5 download)

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Book Synopsis VLSI and Hardware Implementations using Modern Machine Learning Methods by : Sandeep Saini

Download or read book VLSI and Hardware Implementations using Modern Machine Learning Methods written by Sandeep Saini and published by CRC Press. This book was released on 2021-12-31 with total page 292 pages. Available in PDF, EPUB and Kindle. Book excerpt: Machine learning is a potential solution to resolve bottleneck issues in VLSI via optimizing tasks in the design process. This book aims to provide the latest machine-learning–based methods, algorithms, architectures, and frameworks designed for VLSI design. The focus is on digital, analog, and mixed-signal design techniques, device modeling, physical design, hardware implementation, testability, reconfigurable design, synthesis and verification, and related areas. Chapters include case studies as well as novel research ideas in the given field. Overall, the book provides practical implementations of VLSI design, IC design, and hardware realization using machine learning techniques. Features: Provides the details of state-of-the-art machine learning methods used in VLSI design Discusses hardware implementation and device modeling pertaining to machine learning algorithms Explores machine learning for various VLSI architectures and reconfigurable computing Illustrates the latest techniques for device size and feature optimization Highlights the latest case studies and reviews of the methods used for hardware implementation This book is aimed at researchers, professionals, and graduate students in VLSI, machine learning, electrical and electronic engineering, computer engineering, and hardware systems.

Quantum Inspired Meta-heuristics for Image Analysis

Author : Sandip Dey
Publisher : John Wiley & Sons
ISBN 13 : 1119488753
Total Pages : 374 pages
Book Rating : 4.1/5 (194 download)

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Book Synopsis Quantum Inspired Meta-heuristics for Image Analysis by : Sandip Dey

Download or read book Quantum Inspired Meta-heuristics for Image Analysis written by Sandip Dey and published by John Wiley & Sons. This book was released on 2019-08-05 with total page 374 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Optimization Models in Steganography Using Metaheuristics

Author : Dipti Kapoor Sarmah
Publisher : Springer Nature
ISBN 13 : 3030420442
Total Pages : 174 pages
Book Rating : 4.0/5 (34 download)

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Book Synopsis Optimization Models in Steganography Using Metaheuristics by : Dipti Kapoor Sarmah

Download or read book Optimization Models in Steganography Using Metaheuristics written by Dipti Kapoor Sarmah and published by Springer Nature. This book was released on 2020-02-25 with total page 174 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book explores the use of a socio-inspired optimization algorithm (the Cohort Intelligence algorithm), along with Cognitive Computing and a Multi-Random Start Local Search optimization algorithm. One of the most important types of media used for steganography is the JPEG image. Considering four important aspects of steganography techniques – picture quality, high data-hiding capacity, secret text security and computational time – the book provides extensive information on four novel image-based steganography approaches that employ JPEG compression. Academics, scientists and engineers engaged in research, development and application of steganography techniques, optimization and data analytics will find the book’s comprehensive coverage an invaluable resource.