Image Retrieval
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Image Retrieval And Analysis Using Text And Fuzzy Shape Features Emerging Research And Opportunities
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Author : Sumathy, P.
language : en
Publisher: IGI Global
Release Date : 2018-01-05
Image Retrieval And Analysis Using Text And Fuzzy Shape Features Emerging Research And Opportunities written by Sumathy, P. and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-01-05 with Computers categories.
Multimedia information retrieval focuses on the tools of processing and searching that are applicable to the content-based management of new multimedia documents. It has recently expanded to encompass newly devised techniques that will further its performance and growing importance. Image Retrieval and Analysis Using Text and Fuzzy Shape Features: Emerging Research and Opportunities is a critical scholarly resource that explores methods and strategies related to multimedia information retrieval systems. Featuring coverage on a broad range of topics including content-based image retrieval, text-based image retrieval, fuzzy object shape features, encoding, and indexing, this book is geared towards library science specialists, information technology specialists, and researchers seeking current information on the integration of new information retrieval technologies.
Content Based Image Retrieval
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Author : Vipin Tyagi
language : en
Publisher: Springer
Release Date : 2018-01-15
Content Based Image Retrieval written by Vipin Tyagi and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-01-15 with Computers categories.
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.
Multimedia Systems And Content Based Image Retrieval
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Author : Sagarmay Deb
language : en
Publisher: IGI Global
Release Date : 2004-01-01
Multimedia Systems And Content Based Image Retrieval written by Sagarmay Deb and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2004-01-01 with Technology & Engineering categories.
Business intelligence has always been considered an essential ingredient for success. However, it is not until recently that the technology has enabled organizations to generate and deploy intelligence for global competition. These technologies can be leveraged to create the intelligent enterprises of the 21st century that will not only provide excellent and customized services to their customers, but will also create business efficiency for building relationships with suppliers and other business partners on a long term basis. Creating such intelligent enterprises requires the understanding and integration of diverse enterprise components into cohesive intelligent systems. Anticipating that future enterprises need to become intelligent, Intelligent Enterprises of the 21st Century brings together the experiences and knowledge from many parts of the world to provide a compendium of high quality theoretical and applied concepts, methodologies, and techniques that help diffuse knowledge and skills required to create and manage intelligent enterprises of the 21st century for gaining sustainable competitive advantage in a global environment. This book is a comprehensive compilation of the state of the art vision and thought processes needed to design and manage globally competitive business organizations.
Content Based Image Retrieval
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Author : Fouad Sabry
language : en
Publisher: One Billion Knowledgeable
Release Date : 2024-05-09
Content Based Image Retrieval written by Fouad Sabry and has been published by One Billion Knowledgeable this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-05-09 with Computers categories.
What is Content Based Image Retrieval Content-based image retrieval, also known as query by image content and content-based visual information retrieval (CBVIR), is the application of computer vision techniques to the problem of image retrieval, which is the difficulty of searching for digital images in big databases. Other names for this technique include content-based visual information retriev. In contrast to the conventional concept-based methods, content-based picture retrieval is a more recent development. How you will benefit (I) Insights, and validations about the following topics: Chapter 1: Content-based image retrieval Chapter 2: Information retrieval Chapter 3: Image retrieval Chapter 4: Automatic image annotation Chapter 5: Tag cloud Chapter 6: Video search engine Chapter 7: Image organizer Chapter 8: Image meta search Chapter 9: Reverse image search Chapter 10: Visual search engine (II) Answering the public top questions about content based image retrieval. (III) Real world examples for the usage of content based image retrieval in many fields. Who this book is for Professionals, undergraduate and graduate students, enthusiasts, hobbyists, and those who want to go beyond basic knowledge or information for any kind of Content Based Image Retrieval.
Integrated Region Based Image Retrieval
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Author : James Z. Wang
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-12-06
Integrated Region Based Image Retrieval written by James Z. Wang and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-12-06 with Computers categories.
Content-based image retrieval is the set of techniques for retrieving relevant images from an image database on the basis of automatically derived image features. The need for efficient content-based image re trieval has increased tremendously in many application areas such as biomedicine, the military, commerce, education, and Web image clas sification and searching. In the biomedical domain, content-based im age retrieval can be used in patient digital libraries, clinical diagnosis, searching of 2-D electrophoresis gels, and pathology slides. I started my work on content-based image retrieval in 1995 when I was with Stanford University. The project was initiated by the Stan ford University Libraries and later funded by a research grant from the National Science Foundation. The goal was to design and implement a computer system capable of indexing and retrieving large collections of digitized multimedia data available in the libraries based on the media contents. At the time, it seemed reasonable to me that I should discover the solution to the image retrieval problem during the project. Experi ence has certainly demonstrated how far we are as yet from solving this basic problem.
Artificial Intelligence For Maximizing Content Based Image Retrieval
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Author : Ma, Zongmin
language : en
Publisher: IGI Global
Release Date : 2009-01-31
Artificial Intelligence For Maximizing Content Based Image Retrieval written by Ma, Zongmin and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2009-01-31 with Computers categories.
Discusses major aspects of content-based image retrieval (CBIR) using current technologies and applications within the artificial intelligence (AI) field.
Image Retrieval
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Author : Corinne Jörgensen
language : en
Publisher: Bloomsbury Publishing PLC
Release Date : 2003
Image Retrieval written by Corinne Jörgensen and has been published by Bloomsbury Publishing PLC this book supported file pdf, txt, epub, kindle and other format this book has been release on 2003 with Art categories.
When you hear the term "image management," do you think of making a good impression? Or taking good care of Impressionists? If the latter, this book is for you Vast collections of images exist in a wide range of organizations and institutions, and on the Internet. Some of these images are difficult to track down; others are just too large, too small, too valuable, or too fragile to access directly. In this introductory text to the field, Jorgensen describes the theoretical, empirical, and pragmatic underpinnings of storage and retrieval as they apply to a variety of visual formats.
Feature Extraction In Medical Image Retrieval
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Author : Aswini Kumar Samantaray
language : en
Publisher: Springer Nature
Release Date : 2024-05-15
Feature Extraction In Medical Image Retrieval written by Aswini Kumar Samantaray and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-05-15 with Computers categories.
Medical imaging is fundamental to modern healthcare, and its widespread use has resulted in creation of image databases. These repositories contain images from a diverse range of modalities, multidimensional as well as co-aligned multimodality images. These image collections offer opportunity for evidence-based diagnosis, teaching, and research. Advances in medical image analysis over last two decades shows there are now many algorithms and ideas available that allow to address medical image analysis tasks in commercial solutions with sufficient performance in terms of accuracy, reliability and speed. Content-based image retrieval (CBIR) is an image search technique that complements the conventional text-based retrieval of images by using visual features, such as color, texture, and shape, as search criteria. This book emphasizes the design of wavelet filter-banks as efficient and effective feature descriptors for medical image retrieval. Firstly, a generalized novel design of a family of multiplier-free orthogonal wavelet filter-banks is presented. In this, the dyadic filter coefficients are obtained based on double-shifting orthogonality property with allowable deviation from original filter coefficients. Next, a low complex symmetric Daub-4 orthogonal wavelet filter-bank is presented. This is achieved by slightly altering the perfect reconstruction condition to make designed filter-bank symmetric and to obtain dyadic filter coefficients. In third contribution, the first dyadic Gabor wavelet filter-bank is presented based on slight alteration in orientation parameter without disturbing remaining Gabor wavelet parameters. In addition, a novel feature descriptor based on the design of adaptive Gabor wavelet filter-bank is presented. The use of Maximum likelihood estimation is suggested to measure the similarity between the feature vectors of heterogeneous medical images. The performance of the suggested methods is evaluated on three different publicly available databases namely NEMA, OASIS and EXACT09. The performance in terms of average retrieval precision, average retrieval recall and computational time are compared with well-known existing methods.
Intelligent Image Databases
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Author : Yihong Gong
language : en
Publisher: Springer Science & Business Media
Release Date : 1997-10-31
Intelligent Image Databases written by Yihong Gong and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 1997-10-31 with Computers categories.
Intelligent Image Databases: Towards Advanced Image Retrieval addresses the image feature selection issue in developing content-based image retrieval systems. The book first discusses the four important issues in developing a complete content-based image retrieval system, and then demonstrates that image feature selection has significant impact on the remaining issues of system design. Next, it presents an in-depth literature survey on typical image features explored by contemporary content-based image retrieval systems for image matching and retrieval purposes. The goal of the survey is to determine the characteristics and the effectiveness of individual features, so as to establish guidelines for future development of content-based image retrieval systems. Intelligent Image Databases: Towards Advanced Image Retrieval describes the Advanced Region-Based Image Retrieval System (ARBIRS) developed by the authors for color images of real-world scenes. They have selected image regions for building ARBIRS as the literature survey suggests that prominent image regions, along with their associated features, provide a higher probability for achieving a higher level content-based image retrieval system. A major challenge in building a region-based image retrieval system is that prominent regions are rather difficult to capture in an accurate and error-free condition, particularly those in images of real-world scenes. To meet this challenge, the book proposes an integrated approach to tackle the problem via feature capturing, feature indexing, and database query. Through comprehensive system evaluation, it is demonstrated how these systematically integrated efforts work effectively to accomplish advanced image retrieval. Intelligent Image Databases: Towards Advanced Image Retrieval serves as an excellent reference and may be used as a text for advanced courses on the topic.
Experiment And Evaluation In Information Retrieval Models
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Author : K. Latha
language : en
Publisher: CRC Press
Release Date : 2017-07-28
Experiment And Evaluation In Information Retrieval Models written by K. Latha and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-07-28 with Computers categories.
Experiment and Evaluation in Information Retrieval Models explores different algorithms for the application of evolutionary computation to the field of information retrieval (IR). As well as examining existing approaches to resolving some of the problems in this field, results obtained by researchers are critically evaluated in order to give readers a clear view of the topic. In addition, this book covers Algorithmic Solutions to the Problems in Advanced IR Concepts, including Feature Selection for Document Ranking, web page classification and recommendation, Facet Generation for Document Retrieval, Duplication Detection and seeker satisfaction in question answering community Portals. Written with students and researchers in the field on information retrieval in mind, this book is also a useful tool for researchers in the natural and social sciences interested in the latest developments in the fast-moving subject area. Key features: Focusing on recent topics in Information Retrieval research, Experiment and Evaluation in Information Retrieval Models explores the following topics in detail: Searching in social media Using semantic annotations Ranking documents based on Facets Evaluating IR systems offline and online The role of evolutionary computation in IR Document and term clustering, Image retrieval Design of user profiles for IR Web page classification and recommendation Relevance feedback approach for Document and image retrieval