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Content-Based Image Retrieval

Author : Vipin Tyagi

Publisher : Springer

Page : 399 pages

File Size : 38,17 MB

Release : 2018-01-15

Category : Computers

ISBN : 9811067597

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Book Description

The book describes several techniques used to bridge the semantic gap and reflects on recent advancements in content-based image retrieval (CBIR). It presents insights into and the theoretical foundation of various essential concepts related to image searches, together with examples of natural and texture image types. The book discusses key challenges and research topics in the context of image retrieval, and provides descriptions of various image databases used in research studies. The area of image retrieval, and especially content-based image retrieval (CBIR), is a very exciting one, both for research and for commercial applications. The book explains the low-level features that can be extracted from an image (such as color, texture, shape) and several techniques used to successfully bridge the semantic gap in image retrieval, making it a valuable resource for students and researchers interested in the area of CBIR alike.



Computer Vision Methods for Fast Image Classification and Retrieval

Author : Rafał Scherer

Publisher : Springer

Page : 144 pages

File Size : 25,79 MB

Release : 2019-01-29

Category : Technology & Engineering

ISBN : 303012195X

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Book Description

The book presents selected methods for accelerating image retrieval and classification in large collections of images using what are referred to as ‘hand-crafted features.’ It introduces readers to novel rapid image description methods based on local and global features, as well as several techniques for comparing images. Developing content-based image comparison, retrieval and classification methods that simulate human visual perception is an arduous and complex process. The book’s main focus is on the application of these methods in a relational database context. The methods presented are suitable for both general-type and medical images. Offering a valuable textbook for upper-level undergraduate or graduate-level courses on computer science or engineering, as well as a guide for computer vision researchers, the book focuses on techniques that work under real-world large-dataset conditions.





Content-Based Image and Video Retrieval

Author : Oge Marques

Publisher : Springer Science & Business Media

Page : 189 pages

File Size : 41,96 MB

Release : 2012-12-06

Category : Computers

ISBN : 1461509874

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Book Description

Content-Based Image And Video Retrieval addresses the basic concepts and techniques for designing content-based image and video retrieval systems. It also discusses a variety of design choices for the key components of these systems. This book gives a comprehensive survey of the content-based image retrieval systems, including several content-based video retrieval systems. The survey includes both research and commercial content-based retrieval systems. Content-Based Image And Video Retrieval includes pointers to two hundred representative bibliographic references on this field, ranging from survey papers to descriptions of recent work in the area, entire books and more than seventy websites. Finally, the book presents a detailed case study of designing MUSE–a content-based image retrieval system developed at Florida Atlantic University in Boca Raton, Florida.



State-of-the-Art in Content-Based Image and Video Retrieval

Author : Remco C. Veltkamp

Publisher : Springer Science & Business Media

Page : 349 pages

File Size : 11,55 MB

Release : 2013-04-17

Category : Computers

ISBN : 9401596646

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Book Description

Images and video play a crucial role in visual information systems and multimedia. There is an extraordinary number of applications of such systems in entertainment, business, art, engineering, and science. Such applications often involved large image and video collections, and therefore, searching for images and video in large collections is becoming an important operation. Because of the size of such databases, efficiency is crucial. We strongly believe that image and video retrieval need an integrated approach from fields such as image processing, shape processing, perception, database indexing, visualization, and querying, etc. This book contains a selection of results that was presented at the Dagstuhl Seminar on Content-Based Image and Video Retrieval, in December 1999. The purpose of this seminar was to bring together people from the various fields, in order to promote information exchange and interaction among researchers who are interested in various aspects of accessing the content of image and video data. The book provides an overview of the state of the art in content-based image and video retrieval. The topics covered by the chapters are integrated system aspects, as well as techniques from image processing, computer vision, multimedia, databases, graphics, signal processing, and information theory. The book will be of interest to researchers and professionals in the fields of multimedia, visual information (database) systems, computer vision, and information retrieval.



Symbolic Projection for Image Information Retrieval and Spatial Reasoning

Author : Shi-Kuo Chang

Publisher : Elsevier

Page : 339 pages

File Size : 32,52 MB

Release : 1996-04-02

Category : Computers

ISBN : 0080542166

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Book Description

Information systems with an abundance of graphics data are growing rapidly due to advances in data storage technology, the development of multimedia communications across networks, and the fact that parallel computers are leading to faster image processing systems. This book addresses image information retrieval and spatial reasoning using an approach called Symbolic Projection, which supports descriptions of the image content on the basis of the spatial relationships between the pictorial objects. Image information systems have a wide variety of applications, including information retrieval on the World Wide Web, medical pictorial archiving, computer-aided design, robotics, and geographical information systems, and this book is comprehensively illustrated with examples from these areas. Symbolic Projection now forms the basis of an enormous number and range of information retrieval algorithms, and also supports query-by-picture and qualitative spatial reasoning. Both authors are international experts in the field, and the book will serve as an excellent source for those working in multimedia systems and image information systems who wish to find out more about this exciting area. - An all-inclusive source to the field--all you need to know - S-K. Chang is the leading authority in this field, which he pioneered - Includes a wide variety of applications, including information retrieval on the World Wide Web, computer-aided design, and geographical information systems



Images in Social Media

Author : Susanne Ørnager

Publisher : Morgan & Claypool Publishers

Page : 121 pages

File Size : 42,96 MB

Release : 2018-02-06

Category : Computers

ISBN : 1681730804

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Book Description

This book focuses on the methodologies, organization, and communication of digital image collection research that utilizes social media content. ("Image" is here understood as a cultural, conventional, and commercial—stock photo—representation.) The lecture offers expert views that provide different interpretations of images and their potential implementations. Linguistic and semiotic methodologies as well as eye-tracking research are employed to both analyze images and comprehend how humans consider them, including which salient features generally attract viewers' attention. This literature review covers image—specifically photographic—research since 2005, when major social media platforms emerged. A citation analysis includes an overview of co-citation maps that demonstrate the nexus of image research literature and the journals in which they appear. Eye tracking tests whether scholarly templates focus on the proper features of an image, such as people, objects, time, etc., and if a prescribed theme affects the eye movements of the observer. The results may point to renewed requirements for building image search engines. As it stands, image management already requires new algorithms and a new understanding that involves text recognition and very large database processing. The aim of this book is to present different image research areas and demonstrate the challenges image research faces. The book's scope is, by necessity, far from comprehensive, since the field of digital image research does not cover fake news, image manipulation, mobile photos, etc.; these issues are very complex and need a publication of their own. This book should primarily be useful for students in library and information science, psychology, and computer science.



Machine Learning and Statistical Modeling Approaches to Image Retrieval

Author : Yixin Chen

Publisher : Springer Science & Business Media

Page : 194 pages

File Size : 24,48 MB

Release : 2004-05-27

Category : Technology & Engineering

ISBN : 1402080344

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Book Description

In the early 1990s, the establishment of the Internet brought forth a revolutionary viewpoint of information storage, distribution, and processing: the World Wide Web is becoming an enormous and expanding distributed digital library. Along with the development of the Web, image indexing and retrieval have grown into research areas sharing a vision of intelligent agents. Far beyond Web searching, image indexing and retrieval can potentially be applied to many other areas, including biomedicine, space science, biometric identification, digital libraries, the military, education, commerce, culture and entertainment. Machine Learning and Statistical Modeling Approaches to Image Retrieval describes several approaches of integrating machine learning and statistical modeling into an image retrieval and indexing system that demonstrates promising results. The topics of this book reflect authors' experiences of machine learning and statistical modeling based image indexing and retrieval. This book contains detailed references for further reading and research in this field as well.



Exploratory Image Databases

Author : Simone Santini

Publisher : Elsevier

Page : 637 pages

File Size : 31,94 MB

Release : 2001-09-05

Category : Computers

ISBN : 0080506151

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Book Description

The explosion of computer use and internet communication has placed new emphasis on the ability to store, retrieve and search for all types of images, both still photo and video images. The success and the future of visual information retrieval depends on the cutting edge research and applications explored in this book. It combines the expertise from both computer vision and database research.Unlike text retrieval and text/numeric databases the challenges of image databases are enormous. How do you use "data mining" to search for an image if you do not have "key words" to search? Exploratory Image Databases introduces the idea that it is possible to solve this problem by merging database systems into a single search and browse activity called "exploration."Exploratory Image Databases is one of the first single-author books that unifies the critical emerging topic of image databases. A new approach to image databases, the work is divided into four central parts: introduction to the problems that image database research must solve; computer vision and information retrieval techniques; image database issues; and interface and engines for visual searches.Example: Imagine the difficulty of building and using a database for "face recognition," where an image of a face is used. In order to effectively use the image a huge number of characteristics would need to be entered in the database. The goal of future image databases is to use hardware and software to recognize and categorize images without typing in characteristics.* Comprehensive coverage of the image analysis as well as the database/theoretical aspects of image databases. * Extensive coverage of interfaces and interaction models, with a theoretical framework for the development of new interaction schemes. * Identifies three interaction models between users and image databases, two of which have no counterpart in traditional databases. * Coverage of the relation between image and text, including mixed search models and the automatic determination of the relation between images and text on large corpuses like the web. * Analysis of the process of signification in images and its influence on the interaction models and technological problems of image databases.



Artificial Intelligence for Maximizing Content Based Image Retrieval

Author : Ma, Zongmin

Publisher : IGI Global

Page : 450 pages

File Size : 44,96 MB

Release : 2009-01-31

Category : Computers

ISBN : 1605661759

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Book Description

Discusses major aspects of content-based image retrieval (CBIR) using current technologies and applications within the artificial intelligence (AI) field.