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检索条件"任意字段=Conference on Storage and Retrieval for Image and Video Databases III"

共 344 条记录，以下是291-300 订阅

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EMBEDDING image QUERY OPERATIONS IN AN OBJECT-RELATIONAL DATABASE MANAGEMENT SYSTEM

EMBEDDING IMAGE QUERY OPERATIONS IN AN OBJECT-RELATIONAL DAT...

引用

conference on storage and retrieval for image and video databases iii

作者： UBELL, M OLSON, M ILLUSTRA INFORMAT TECHNOL INC OAKLANDCA 94607

ISBN: (纸本)081941767X

Modern computer applications use enormous volumes of rich data like video, still images, and text, as well as more conventional numeric and character data. Managing huge volumes of such diverse data requires a database. Content queries, such as 'find me the color images with red components higher than this threshold,' require that the database system be able to apply the qualification directly. Relational database systems that store images as untyped binary large objects (BLOBS) cannot apply qualifications like this, because the database system does not understand the contents of the BLOB. Object-Relational Database Management Systems (ORDBMS), on the other hand, allow users to extend the set of types and functions known to the database system. Programmers can write code that is dynamically loaded into the database server, and that operates on complex data types such as images. Those functions can be used in standard SQL queries, and the database manager can use new types and function results in indices to support fast queries on complex data. In addition, the query optimizer can be told how expensive the new functions are, so that it chooses an optimal strategy for satisfying complicated queries with many different predicates in their qualifications.

关键词： OBJECT RELATIONAL DATABASE image QUERY image storage

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Adaptive filtering and indexing for image databases

Adaptive filtering and indexing for image databases

引用

storage and retrieval for image and video databases iii

作者： Alexandrov, A. Ma, W.Y. El Abbadi, Amr Manjunath, B.S. Univ. of California/Santa Barbara Santa Barbara CA USA United States

ISBN: (纸本)081941767X

In this paper we combine image feature extraction with indexing techniques for efficient retrieval in large texture images databases. A 2D image signal is processed using a set of Gabor filters to derive a 120 component feature vector representing the image. The feature components are ordered based on the relative importance in characterizing a given texture pattern, and this facilitates the development of efficient indexing mechanisms. We propose three different sets of indexing features based on the best feature, the average feature and a combination of both. We investigate the tradeoff between accuracy and discriminating power using these different indexing approaches, and conclude that the combination of best feature and the average feature gives the best results.

关键词： Database systems

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System for indexing multispectral satellite images for efficient content-based retrieval

System for indexing multispectral satellite images for effic...

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storage and retrieval for image and video databases iii

作者： Barros, Julio E. French, James C. Martin, Worthy N. Kelly, Patrick M. Univ. of Virginia Charlottesville VA USA United States

ISBN: (纸本)081941767X

Current feature-based image databases can typically perform efficient and effective searches on scalar feature information. However, many important features, such as graphs, histograms, and probability density functions, have more complex structure. Mechanisms to manipulate complex feature data are not currently well understood and must be further developed. The work we discuss in this paper explores techniques for the exploitation of spectral distribution information in a feature-based image database. A six band image was segmented into regions and spectral information for each region was maintained. A similarity measure for the spectral information is proposed and experiments are conducted to test its effectiveness. The objective of our current work is to determine if these techniques are effective and efficient at managing this type of image feature data.

关键词： Indexing (of information)

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Similarity measures for image databases

引用

storage and retrieval for image and video databases iii

作者： Jain, Ramesh C. Murthy, S.N. Tran, Luong Chatterjee, Shankar Univ. of California/San Diego La Jolla CA USA United States

ISBN: (纸本)081941767X

Similarity between images is used for storage and retrieval in image databases. In the literature, several similarity measures have been proposed that may be broadly categorized as: (1) metric based, (2) set-theoretic based, and (3) decision-theoretic based measures. In each category, measured based on crisp logic as well as fuzzy logic are available. In some applications such as image databases, measures based on fuzzy logic would appear to be naturally better suited, although so far no comprehensive experimental study has been undertaken. In this paper, we report results of some of the experiments designed to compare various similarity measures for application to image databases. We are currently working with texture images and intend to work with face images in the near future. As a first step for comparison, the similarity matrices for each of the similarity measures are computed over a set of selected textures and are presented as visual images. Comparative analysis of these images reveals the relative characteristics of each of these measures. Further experiments are needed to study their sensitivity to small changes in images such as illumination, magnification, orientation, etc. We describe these experiments (sensitivity analysis, transition analysis, etc.) that are currently in progress. The results from these experiments offer assistance in choosing the appropriate measure for applications to image databases.

关键词： Database systems

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Semiautomatic video database system

Semiautomatic video database system

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storage and retrieval for image and video databases iii

作者： Devadiga, Sadashiva Koshiba, D.A. Gargi, U. Oswald, S. Kasturi, Rangachar The Pennsylvania State Univ. University Park PA USA United States

ISBN: (纸本)081941767X

We present a prototype video database system designed to accept video sequences as well as still images. The system indexes these sequences based on scene changes, creates a primitive structure of these sequences, and searches this structure for queried objects using specific color features. A video sequence input to the database is first indexed into subsequences using a color histogram difference method. A hierarchical structure is created by thresholding the sequences at various levels of inter-frame difference. For every subsequence that is identified, the first frame in that subsequence, the representative frame, is entered into the database. The system then automatically generates a description for the frame in terms of its color histogram features. Subsequently, the video sequence may be searched for objects (specified as regions of other video sequence frames or still images) using color similarity matching.

关键词： Database systems

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Automatic and semiautomatic methods for image annotation and retrieval in query by image content (QBIC)

Automatic and semiautomatic methods for image annotation and...

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storage and retrieval for image and video databases iii

作者： Ashley, Jon Barber, Ron Flickner, Myron D. Hafner, James L. Lee, Dennis Niblack, Wayne Petkovic, Dragutin IBM Almaden Research Cent. San Jose CA USA United States

ISBN: (纸本)081941767X

Advances in technologies for scanning, networking, and CD-ROM, lower prices for large disk storage, and acceptance of common image compression and file formats have contributed to an increase in the number, size, and uses of on-line image collections. New tools are needed to help users create, manage, and retrieve images from these collections. We are developing QBIC (query by image content), a prototype system that allows a user to create and query image databases in which the image content - the colors, textures, shapes, and layout of images and the objects they contain - is used as the basis of queries. This paper describes two sets of algorithms in QBIC. The first are methods that allow `query by color drawing,' a form of query in which a user draws an approximate color version of an image, and similar images are retrieved. These are automatic algorithms in the sense that no user action is necessary during database population. Secondly, we describe algorithms for semi-automatic identification of image objects during database population, improving the speed and usability of this manually-intensive step. Once outlined, detailed queries on the content-properties of these individual objects can be made at query time.

关键词： image processing

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video query formulation

Video query formulation

引用

storage and retrieval for image and video databases iii

作者： Ahanger, Gulrukh Benson, Dan Little, Thomas D. Boston Univ. Boston MA USA

ISBN: (纸本)081941767X

For developing advanced query formulation methods for general multimedia data, we describe the issues related to video data. We distinguish between the requirements for image retrieval and video retrieval by identifying queryable attributes unique to video data, namely audio, temporal structure, motion, and events. Our approach is based on visual query methods to describe predicates interactively while providing feedback that is as similar as possible to the video data. An initial prototype of our visual query system for video data is presented.

关键词： video signal processing

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Searching images using Ultimedia Manager

Searching images using Ultimedia Manager

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storage and retrieval for image and video databases iii

作者： Treat, H. Ort, Ed Ho, J. Vo, M. Jang, J.S. Hall, L. Tung, F. Petkovic, Dragutin IBM Santa Teresa Lab. San Jose CA USA United States

ISBN: (纸本)081941767X

IBM's Ultimedia Manager is a software product for management and retrieval of image data. The product includes both traditional database search and content based search. Traditional database search allows images to be retrieved by text descriptors or business data such as price, date, and catalog number. Content based search allows retrieval by similarity to a specified color, texture, shape, position or any combination of these. The two can be combined, as in 'retrieve all images with the text `beach' in their description, and sort them in order by how much blue they contain.' Functions are also available for fast browning, and for database navigation. The two main components of Ultimedia Manger are a database population tool to prepare images for query by identifying areas of interest and computing their features, and the query tool for doing retrievals. Application areas include stock photography, electronic libraries, retail, cataloging, and business graphics.

关键词： Information retrieval systems

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Evaluation of video sequence indexing and hierarchical video indexing

Evaluation of video sequence indexing and hierarchical video...

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storage and retrieval for image and video databases iii

作者： Gargi, U. Oswald, S. Koshiba, D.A. Devadiga, Sadashiva Kasturi, Rangachar The Pennsylvania State Univ. University Park PA USA United States

ISBN: (纸本)081941767X

As a first step to creating a video database, a video sequence has to be segmented into several subsequences based on significant changes in the scene. This enables the media user to identify the whole or a part of the sequence and to retrieve scenes of interest from a large video database. Researchers in the past have used a histogram based inter-frame difference approach to identify significant scene changes. To determine which is the best color coordinate system for video indexing, we have evaluated the histogram based indexing method using different color coordinate systems - RGB, HSV, YIQ, L*a*b*, L*u*v* & Munsell - and compared the results for accuracy of indexing with reference to subjective indexing. Since it is difficult to determine the exact threshold value to obtain reasonably good results, we also propose a vide segmenting method called hierarchical histogram based indexing that segments a video sequence into several levels of subsequences using different levels of threshold.

关键词： video signal processing

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Indexing in video databases

Indexing in video databases

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storage and retrieval for image and video databases iii

作者： Hampapur, Arun Jain, Ramesh C. Weymouth, Terry E. Univ. of Michigan Ann Arbor MI USA

ISBN: (纸本)081941767X

A video database provides content based access to video. This is achieved by organizing or indexing video data based on some set of features. This paper defines the problem of video indexing based on video data models. The procedure required to index video data is outlined. The use of semi-automatic techniques to speed up the indexing processes are explored. These techniques use image motion features to aid in the indexing process. The techniques developed have been applied to video data from cable television feed.

关键词： Indexing (of information)

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