Image Databases
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Exploratory Image Databases
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.
Image Databases And Multi-media Search
The World Wide Web and the Internet are signs that things will be very different in the future. And what is so striking about this computer-age future is that it comes incredibly fast and is incredibly overwhelming. Anyone who has surfed the Web has exclaimed at one point or another that there is so much information available, so much to search and so much to keep up with.Where Lycos and AltaVista are already accepted tools for textual information, image and multimedia search engines are the natural answers in the quest for pictorial information. This book provides a state-of-the-art description of that field. It contains the proceedings of a valuable workshop in Amsterdam, where people gathered to discuss the progress in the field. The topics cover computational methods of searching for pictures, the powerful pictorial clues in the recognition of objects, storage and indexing of objects in a database, and, ways to access the requested pictorial information.
Medical Image Databases
Author: Stephen T.C. Wong
language: en
Publisher: Springer Science & Business Media
Release Date: 2012-12-06
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.
