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Clustering Techniques for Image Segmentation, Siddiqui


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Автор: Siddiqui
Название:  Clustering Techniques for Image Segmentation
ISBN: 9783030812324
Издательство: Springer
Классификация:



ISBN-10: 3030812324
Обложка/Формат: Soft cover
Страницы: 108
Вес: 0.25 кг.
Дата издания: 13.11.2022
Язык: English
Издание: 1st ed. 2022
Иллюстрации: 50 tables, color; 16 illustrations, color; 39 illustrations, black and white; xx, 108 p. 55 illus., 16 illus. in color.
Размер: 235 x 155
Читательская аудитория: Professional & vocational
Основная тема: Engineering
Ссылка на Издательство: Link
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Поставляется из: Германии
Описание: This book presents the workings of major clustering techniques along with their advantages and shortcomings. After introducing the topic, the authors illustrate their modified version that avoids those shortcomings. The book then introduces four modified clustering techniques, namely the Optimized K-Means (OKM), Enhanced Moving K-Means-1(EMKM-1), Enhanced Moving K-Means-2(EMKM-2), and Outlier Rejection Fuzzy C-Means (ORFCM). The authors show how the OKM technique can differentiate the empty and zero variance cluster, and the data assignment procedure of the K-mean clustering technique is redesigned. They then show how the EMKM-1 and EMKM-2 techniques reform the data-transferring concept of the Adaptive Moving K-Means (AMKM) to avoid the centroid trapping problem. And that the ORFCM technique uses the adaptable membership function to moderate the outlier effects on the Fuzzy C-meaning clustering technique. This book also covers the working steps and codings of quantitative analysis methods. The results highlight that the modified clustering techniques generate more homogenous regions in an image with better shape and sharp edge preservation. * Showcases major clustering techniques, detailing their advantages and shortcomings; * Includes several methods for evaluating the performance of segmentation techniques; * Presents several applications including medical diagnosis systems, satellite imaging systems, and biometric systems.
Дополнительное описание: Introduction.- Introduction to Image Segmentation and Clustering.- Hard and Soft Clustering Techniques.- New Enhanced Clustering Techniques.- Mathematical Model of clustering techniques and evaluation methods.- Conclusion.



Image Co-segmentation

Автор: Hati
Название: Image Co-segmentation
ISBN: 9811985693 ISBN-13(EAN): 9789811985690
Издательство: Springer
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Цена: 18167.00 р.
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Описание: This book presents and analyzes methods to perform image co-segmentation. In this book, the authors describe efficient solutions to this problem ensuring robustness and accuracy, and provide theoretical analysis for the same. Six different methods for image co-segmentation are presented. These methods use concepts from statistical mode detection, subgraph matching, latent class graph, region growing, graph CNN, conditional encoder–decoder network, meta-learning, conditional variational encoder–decoder, and attention mechanisms. The authors have included several block diagrams and illustrative examples for the ease of readers. This book is a highly useful resource to researchers and academicians not only in the specific area of image co-segmentation but also in related areas of image processing, graph neural networks, statistical learning, and few-shot learning.

Mixed Raster Content

Автор: George Pavlidis
Название: Mixed Raster Content
ISBN: 981102829X ISBN-13(EAN): 9789811028298
Издательство: Springer
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Цена: 22359.00 р.
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Описание: This book presents the main concepts in handling digital images of mixed content, traditionally referenced as mixed raster content (MRC), in two main parts. The first includes introductory chapters covering the scientific and technical background aspects, whereas the second presents a set of research and development approaches to tackle key issues in MRC segmentation, compression and transmission.The book starts with a review of color theory and the mechanism of color vision in humans. In turn, the second chapter reviews data coding and compression methods so as to set the background and demonstrate the complexity involved in dealing with MRC. Chapter three addresses the segmentation of images through an extensive literature review, which highlights the various approaches used to tackle MRC segmentation.The second part of the book focuses on the segmentation of color images for optimized compression, including multi-layered decomposition and representation of MRC and the processes that can be employed to optimize the coding rates of those different layers. Rounding out the coverage, the final chapter examines the segmentation of color images for optimized transmission.

Segmentation of Hand Bone for Bone Age Assessment

Автор: Yan Chai Hum
Название: Segmentation of Hand Bone for Bone Age Assessment
ISBN: 9814451657 ISBN-13(EAN): 9789814451659
Издательство: Springer
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Цена: 9794.00 р.
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Описание: The objective of this Brief is to provide a solution to the unsolved technical problem in segmentation for the automated bone age assessment system. It is followed by a novel fuzzy quadruple division scheme to optimize the central segmentation algorithm, and then an additional quality assurance scheme.

Segmentation and Separation of Overlapped Latent Fingerprints

Автор: Branka Stojanovi?; Oge Marques; Aleksandar Ne?kovi
Название: Segmentation and Separation of Overlapped Latent Fingerprints
ISBN: 3030233634 ISBN-13(EAN): 9783030233631
Издательство: Springer
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Цена: 6986.00 р.
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Описание:

This Springerbrief presents an overview of problems and technologies behind segmentation and separation of overlapped latent fingerprints, which are two fundamental steps in the context of fingerprint matching systems. It addresses five main aspects: (1) the need for overlapped latent fingerprint segmentation and separation in the context of fingerprint verification systems; (2) the different datasets available for research on overlapped latent fingerprints; (3) selected algorithms and techniques for segmentation of overlapped latent fingerprints; (4) selected algorithms and techniques for separation of overlapped latent fingerprints; and (5) the use of deep learning techniques for segmentation and separation of overlapped latent fingerprints.
By offering a structured overview of the most important approaches currently available, putting them in perspective, and suggesting numerous resources for further exploration, this book gives its readers a clear path for learning new topics and engaging in related research. Written from a technical perspective, and yet using language and terminology accessible to non-experts, it describes the technologies, introduces relevant datasets, highlights the most important research results in each area, and outlines the most challenging open research questions.
This Springerbrief targets researchers, professionals and advanced-level students studying and working in computer science, who are interested in the field of fingerprint matching and biometrics. Readers who want to deepen their understanding of specific topics will find more than one hundred references to additional sources of related information.
Video Segmentation and Its Applications

Автор: King Ngi Ngan; Hongliang Li
Название: Video Segmentation and Its Applications
ISBN: 1489994661 ISBN-13(EAN): 9781489994660
Издательство: Springer
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Цена: 16977.00 р.
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Описание: This book presents the latest advances in video segmentation and analysis techniques and covers the theoretical approaches, real applications and methods developed in the computer vision and video analysis community.

Metaheuristics for Data Clustering and Image Segmentation

Автор: Meera Ramadas; Ajith Abraham
Название: Metaheuristics for Data Clustering and Image Segmentation
ISBN: 3030040968 ISBN-13(EAN): 9783030040963
Издательство: Springer
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Цена: 13974.00 р.
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Описание: 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.

Interactive Segmentation Techniques

Автор: Jia He; Chang-Su Kim; C.-C. Jay Kuo
Название: Interactive Segmentation Techniques
ISBN: 9814451592 ISBN-13(EAN): 9789814451598
Издательство: Springer
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Цена: 9141.00 р.
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Описание: This book will first introduce classic graph-cut segmentation algorithms and then discuss state-of-the-art techniques, including graph matching methods, region merging and label propagation, clustering methods, and segmentation methods based on edge detection.

Marginal Space Learning for Medical Image Analysis

Автор: Yefeng Zheng; Dorin Comaniciu
Название: Marginal Space Learning for Medical Image Analysis
ISBN: 1493955756 ISBN-13(EAN): 9781493955756
Издательство: Springer
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Цена: 11179.00 р.
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Описание: Automatic detection and segmentation of anatomical structures in medical images are prerequisites to subsequent image measurements and disease quantification, and therefore have multiple clinical applications.

Hybrid Soft Computing for Multilevel Image and Data Segmentation

Автор: Sourav De; Siddhartha Bhattacharyya; Susanta Chakr
Название: Hybrid Soft Computing for Multilevel Image and Data Segmentation
ISBN: 3319475231 ISBN-13(EAN): 9783319475233
Издательство: Springer
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Цена: 13275.00 р.
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Описание: This book explains efficient solutions for segmenting the intensity levels of different types of multilevel images. The authors present hybrid soft computing techniques, which have advantages over conventional soft computing solutions as they incorporate data heterogeneity into the clustering/segmentation procedures.This is a useful introduction and reference for researchers and graduate students of computer science and electronics engineering, particularly in the domains of image processing and computational intelligence.

Hybrid Soft Computing for Image Segmentation

Автор: Siddhartha Bhattacharyya; Paramartha Dutta; Sourav
Название: Hybrid Soft Computing for Image Segmentation
ISBN: 3319472224 ISBN-13(EAN): 9783319472225
Издательство: Springer
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Цена: 15372.00 р.
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Описание: This book proposes soft computing techniques for segmenting real-life images in applications such as image processing, image mining, video surveillance, and intelligent transportation systems. The book suggests hybrids deriving from three main approaches: fuzzy systems, primarily used for handling real-life problems that involve uncertainty; artificial neural networks, usually applied for machine cognition, learning, and recognition; and evolutionary computation, mainly used for search, exploration, efficient exploitation of contextual information, and optimization.The contributed chapters discuss both the strengths and the weaknesses of the approaches, and the book will be valuable for researchers and graduate students in the domains of image processing and computational intelligence.

Image Segmentation and Compression Using Hidden Markov Models

Автор: Jia Li; Robert M. Gray
Название: Image Segmentation and Compression Using Hidden Markov Models
ISBN: 1461370272 ISBN-13(EAN): 9781461370277
Издательство: Springer
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Цена: 20962.00 р.
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Описание: Conventional block-based segmentation algorithms classify each block separately, assuming independence of feature vectors. Image Segmentation and Compression Using Hidden Markov Models presents a new algorithm that models the statistical dependence among image blocks by two dimensional hidden Markov models (HMMs).

Variational and Level Set Methods in Image Segmentation

Автор: Amar Mitiche; Ismail Ben Ayed
Название: Variational and Level Set Methods in Image Segmentation
ISBN: 3642265626 ISBN-13(EAN): 9783642265624
Издательство: Springer
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Цена: 18167.00 р.
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Описание: Image segmentation is used in a wide range of useful applications such as remote sensing, medicine, robotics, database search, and security. The text provides an overview of level set methods for image and image sequence segmentation.


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