Intelligent Image Databases
Intelligent Image Databases

Author: Yihong Gong

Publisher: Springer Science & Business Media

Published: 1997-10-31

Total Pages: 154

ISBN-13: 9780792380153

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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.

Image Databases
Image Databases

Author: Vittorio Castelli

Publisher: John Wiley & Sons

Published: 2004-04-07

Total Pages: 609

ISBN-13: 0471464074

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The explosive growth of multimedia data transmission has generated a critical need for efficient, high-capacity image databases, as well as powerful search engines to retrieve image data from them. This book brings together contributions by an international all-star team of innovators in the field who share their insights into all key aspects of image database and search engine construction. Readers get in-depth discussions of the entire range of crucial image database architecture, indexing and retrieval, transmission, display, and user interface issues. And, using examples from an array of disciplines, the authors present cutting-edge applications in medical imagery, multimedia communications, earth science, remote sensing, and other major application areas.

Medical Image Databases
Medical Image Databases

Author: Stephen T.C. Wong

Publisher: Springer Science & Business Media

Published: 1998-09-30

Total Pages: 420

ISBN-13: 9780792382898

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Medical Image Databases covers the new technologies of biomedical imaging databases and their applications in clinical services, education, and research. Authors were selected because they are doing cutting-edge basic or technology work in relevant areas. This was done to infuse each chapter with ideas from people actively investigating and developing medical image databases rather than simply review the existing literature. The authors have analyzed the literature and have expanded on their own research. They have also addressed several common threads within their generic topics. These include system architecture, standards, information retrieval, data modeling, image visualizations, query languages, telematics, data mining, and decision supports. The new ideas and results reported in this volume suggest new and better ways to develop imaging databases and possibly lead us to the next information infrastructure in biomedicine. Medical Image Databases is suitable as a textbook for a graduate-level course on biomedical imaging or medical image databases, and as a reference for researchers and practitioners in industry.

Image Retrieval
Image Retrieval

Author: Corinne Jörgensen

Publisher: Scarecrow Press

Published: 2003

Total Pages: 366

ISBN-13: 9780810847347

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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.

Perceptual Metrics for Image Database Navigation
Perceptual Metrics for Image Database Navigation

Author: Yossi Rubner

Publisher: Springer Science & Business Media

Published: 2001

Total Pages: 170

ISBN-13: 9780792372196

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With the increasing number of images available electronically, automatic retrieval systems are becoming essential. This book introduces an absolute prerequisite for any such system: a metric, called the Earth Mover's Distance (EMD), for comparing images in terms of their appearance. This metric describes the amount of work that is necessary to transform one image into another, in a precisely defined mathematical sense, and in a flexible and perceptually meaningful manner. An efficient linear programming algorithm enables the computation of this metric fast enough to be used for the interactive retrieval of images from large repositories. The perceptual properties of the EMD, and the speed of its computation, lead to database navigation, a new paradigm for interacting with a repository of images. When navigating, the user is shown a very large number of images in response to a query. The EMD between pairs of images, together with a multidimensional scaling method, allows these images to be displayed so that similar images appear near to each other on the computer screen. In this way, the user can grasp at a glance what is returned, and can reach the images of interest with a small number of mouse clicks. Extensive benchmark evaluations and example retrieval systems show the usefulness of the EMD and the advantages of image database navigation. This book will be of interest to researchers, industrial professionals, and graduate and post-graduate students in the fields of Computer Vision; Image Processing; Data Mining; Digital Libraries; Psychophysics; Computer Science; Electrical Engineering.

Case-Based Reasoning on Images and Signals
Case-Based Reasoning on Images and Signals

Author: Petra Perner

Publisher: Springer Science & Business Media

Published: 2008

Total Pages: 442

ISBN-13: 3540731784

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This book is the ?rst edited book that deals with the special topic of signals and images within case-based reasoning (CBR). Signal-interpreting systems are becoming increasingly popular in medical, industrial, ecological, biotechnological and many other applications. Existing statisticalandknowledge-basedtechniqueslackrobustness,accuracy,and?- ibility. New strategies are needed that can adapt to changing environmental conditions, signal variation, user needs and process requirements. Introducing CBRstrategiesintosignal-interpretingsystemscansatisfytheserequirements. CBR can be used to control the signal-processing process in all phases of a signal-interpreting system to derive information of the highest possible qu- ity. Beyond this CBR o?ers di?erent learning capabilities, for all phases of a signal-interpretingsystem,thatsatisfydi?erentneedsduringthedevelopment process of a signal-interpreting system. In the outline of this book we summarize under the term “signal” signals of 1-dimensional, 2-dimensional or 3-dimensional nature. The unique data and the necessary computation techniques require ext- ordinary case representations, similarity measures and CBR strategies to be utilised. Signalinterpretation(1D,2D,or3Dsignalinterpretation)istheprocessof mapping the numerical representation of a signal into logical representations suitable for signal descriptions. A signal-interpreting system must be able to extract symbolic features from the raw data e.g., the image (e.g., irregular structure inside the nodule, area of calci?cation, and sharp margin). This is a complex process; the signal passes through several general processing steps before the ?nal symbolic description is obtained. The structure of the book is divided into a theoretical part and into an application-oriented part.