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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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videobook: an experiment in characterization of video

Videobook: an experiment in characterization of video

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Proceedings 1996 International Conference on image Processing, ICIP'96

作者： Iyengar, Giridharan Lippman, Andrew B. MIT Media Lab Cambridge MA United States

In this paper we present a framework for content based query and retrieval of information from large video databases. This framework enables content based retrieval of video sequences by characterizing the sequences using motion, texture and colorimetry cues. This characterization is biologically inspired and results in a compact parameter space where every segment of video is represented by an 8 dimensional vector. Searching and retrieval is done in real-time with high accuracy in this parameter space. The present version of the videoBook has 165 video sequences, each 15 seconds long at 30 frames a second representing storage of 65 Giga Bytes. The videoBook is able to search and retrieve video sequences with 92% accuracy in real-time. Experiments thus demonstrate that the characterization is capable of extracting higher level structure from raw pixel values.

关键词： image processing

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Guest Editorial Introduction to the Special Issue on image and video Processing for Digital Libraries

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IEEE Transactions on image Processing 2000年第1期9卷 1-2页

作者： Manjunath, B.S. Huang, T. Tekalp, A.M. Zhang, H.J. University of California Santa Barbara CA 93106 United States University of Illinois at Urbana-Champaign Urbana IL 61801 United States University of Rochester Rochester NY 14627 United States Microsoft Research China Beijing China

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Feature identification as an aid to content-based image retrieval

Feature identification as an aid to content-based image retr...

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storage and retrieval for image and video databases III

作者： Ramesh, Nagarajan Sethi, Ishwar K. Wayne State Univ. Detroit MI USA

ISBN: (纸本)081941767X

In recent years, databases have evolved from storing pure textual information to storing multimedia information - text, audio, video, and images. With such databases comes the need for a richer set of search keys that include keywords, shapes, sounds, examples, sketches, color, texture and motion. In this paper we address the problem of image retrieval where keys are object shapes or user sketches. In our scheme, shape features are extracted from each image as it is stored. The image is first segmented and points of high curvature are extracted. Regions surrounding the points of high curvature are used to compute feature values by comparing the regions with a number of references. The references themselves are picked out from the set of orthonormal wavelet basis vectors. An ordered set of distance measures between each local region and the wavelet references form a feature vector. When a user queries the database through a sketch, the feature vectors for high curvature points on the sketch are determined. An efficient nearest neighbor search then yields a set of images which contain objects that match the user's sketch closely. The process is completely automated. Initial experimental results are presented.

关键词： Information retrieval systems

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MALCBR: Content-based retrieval of image databases at multiple abstraction levels

MALCBR: Content-based retrieval of image databases at multip...

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Conference on Multimedia storage and Archiving Systems II

作者： Castelli, V Li, CS Bergman, LD IBM Thomas J. Watson Research Ctr. (United States)

ISBN: (纸本)0819426628

Content-based search of large image database has received significant attention recently. In this paper, we proposed a new framework, Multiple. Abstraction Level Content Based retrieval (MALCBR), for specifying and process content-based retrieval queries on databases of images, time series, or video data. This framework allows search targets to be expressed in a object-based fashion, that allows the extensible specification of arbitrarily complex queries. In our approach, the search targets are either simple objects, specified at multiple levels of abstraction (pixel, feature and semantic levels), or composite objects, defined as collections of relation on the elements of a set of simple objects. During the search, simple objects at the semantic level are retrieved from database tables, feature level objects are computed using pre-extracted features;appropriately indexed, and pixel level objects are extracted from the raw data. Composite objects are computed at query execution time. This framework provides a powerful mechanism for specifying complicated search target and enable efficient processing of filtering of the search results.

关键词： content-based retrieval image library clustering classification neural networks feature vector template matching

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Two-stage strategy for indexing and presenting video 2

Two-stage strategy for indexing and presenting video

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storage and retrieval for image and video databases II 1994

作者： Cherfaoui, Mourad Bertin, Christian TMM/CCETT 4 rue du Clos courtel Cesson-sevigne35512 France

Owing to the advent of multimedia, simultaneous access 'to text, image, sound, graphics and video has now became been made possible. However, video on computers is a very recent capability. It is achieved thanks to the progress made in hardware components, digitization equipments, storage media (CD ROM) and, above all, image compression techniques (JPEG 1 for still pictures and MPEG 2for motion pictures). The representational power of video makes it the favourite medium for many multimedia applications. The various media are not used in the same way. A structured text (with a table of contents), a still, graphics or sound (with representative graph) may be seen as a whole, allowing them to be handled (for editing purposes for example). Furthermore, these media support information-based navigation (hypertext 3 is a good example of this capability). On the other hand, video is basically a sequential medium. Operations such as fast-forward, rewind and pause allow only limited interactivity when consulting video. This lack of interactivity is due to the fact that video information, unlike structured text, is delivered "flat", with no indications. In order to have the same capacities as in a structured text, it is necessary to have an interpretation level above the raw video information. In the case of structured text, the interpretation level corresponds to paragraph and chapter titles and to the table of contents. Furthermore, text has a basic semantic entity : the word which is used with the search function and the index to create a multiplicity of navigational possibilities through the information. The goal of our work is aimed to offer ways of accessing videos which are similar to those of structured texts. This will make it possible to: .quickly become acquainted with the video content, .quickly access the part of the video of particular interest and .haveentry points in the video. Our methodology is comprised of two stages. In the first stage, we seek to extract t

关键词： video image segmentation Cameras Zoom lenses Visualization image processing video processing video compression image compression Information visualization

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Finding regions of interest for content-extraction

Finding regions of interest for content-extraction

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7th storage and retrieval for image and video databases Conference

作者： Pauwels, EJ Frederix, G Katholieke Univ Leuven ESAT PSI Dept Elect Engn B-3001 Heverlee Belgium

ISBN: (纸本)0819431273

A major problem in Content-Based image retrieval (CBIR) is the unsupervised identification of perceptually salient regions in images. We contend that this problem can be tackled by mapping the pixels into various feature-spaces, whereupon they are subjected to a grouping-algorithm, In this paper we develop a robust and versatile non-parametric clustering algorithm that is able to handle the unbalanced and highly irregular clusters encountered in such CBIR-applications. The strength of our approach lies not so much in the clustering itself, but rather in the definition and use of two duster-validity indices that are independent of the cluster-topology. By combining them, an optimal clustering;can be identified, and experiments confirm that the associated clusters do indeed correspond to perceptually salient image-regions.

关键词： clustering segmentation content-extraction image-retrieval feature-extraction

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Fast encryption of image data using chaotic Kolmogorov flows 5

Fast encryption of image data using chaotic Kolmogorov flows

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Conference on storage and retrieval for image and video databases V

作者： Scharinger, J Johannes Kepler Univ. Linz (Austria)

ISBN: (纸本)0819424331

To guarantee security and privacy A image transmission and archival applications, adequate efficient bulk encryption techniques are necessary which are able to cope with the vast amounts of image data involved. Experience has shown that block-oriented symmetric product ciphers constitute an adequate design paradigm for resolving this task, since they can offer a very high level of security as well as very high encryption rates. In this contribution we introduce a new product cipher which encrypts large blocks of plain-text (images) by repeated intertwined application of substitution and permutation operations. While almost all of the current product ciphers use fixed (predefined) permutation operations on small data blocks, our approach involves parameterizable (keyed) permutations on large data blocks (whole images) induced by specific chaotic systems (Kolmogorov flows). By combining these highly unstable dynamics with an adaption of a very fast shift register based pseudo-random number generator we obtain a new class of computationally secure product ciphers which are firmly grounded on systems theoretic concepts, offering many features that make them superior to contemporary bulk encryption systems when aiming at efficient image data encryption.

关键词： image encryption product ciphers chaotic systems Kolmogorov hows pseudo-random number generation shift registers

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image retrieval in multimedia databases: A survey

Image retrieval in multimedia databases: A survey

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IIH-MSP 2009 - 2009 5th International Conference on Intelligent Information Hiding and Multimedia Signal Processing

作者： Alemu, Yihun Koh, Jong-Bin Ikram, Muhammed Kim, Dong-Kyoo Department of Computer Engineering Ajou University Suwon Korea Republic of

ISBN: (纸本)9780769537627

In the past decades the advancement in the area of database management systems shifts towards multimedia. Multimedia information is very expressive, self explanatory, narrative, etc. Now a day the development of digital media, advanced network infrastructure and the easily available consumer electronics makes the multimedia revolution to run in an alarming rate [4] Inline with the advancement of database technology that incorporates multimedia data, an open question that always rose in the technology is how to retrieve/search images in the multimedia databases. There are a huge number of research works focusing on the searching mechanisms in image databases for efficient retrieval and tried to give supplementary suggestions on the overall systems. The growing of digital medias (digital camera, digital video, digital TV, e-book, cell phones, etc.) gave rise to the revolution of very large multimedia databases, in which the need of efficient storage, organization and retrieval of multimedia contents came into question. Among the multimedia data, this survey paper focuses on the different methods (approaches) and their evaluation techniques used by many of recent research works on image retrieval system. Many researchers develop and use lots of approaches towards image retrieval. This paper, in general, classified image retrieval into text based and content based, including the newly growing ontology based image retrieval system as one focus. We address, in this paper, the challenges, techniques and evaluation methods used in image retrieval systems through a detailed look of most recent works. © 2009 IEEE.

关键词： Digital storage

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Vector angular distance measure for indexing and retrieval of color

Vector angular distance measure for indexing and retrieval o...

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7th storage and retrieval for image and video databases Conference

作者： Androutsos, D Plataniotis, KN Venetsanopoulos, AN Univ Toronto Dept Elect & Comp Engn Digital Signal & Image Proc Lab Toronto ON M5S 3G4 Canada

ISBN: (纸本)0819431273

A key aspect of image retrieval using color, is the creation of robust and efficient indices. In particular, the color histogram remains the most popular index, due primarily to its simplicity. However, the color histogram has a number of drawbacks. Specifically histograms capture only global activity, they require quantisation to reduce dimensionality, are highly dependent on the chosen color space, have no means to exclude a certain color from a query and can provide erroneous results due to gamma nonlinearity. In this paper we present a vector angular distance measure which is implemented as part of our database system. Our system does away with histogram techniques for color indexing and retrieval and instead implements color vector techniques. We use color segmentation to extract regions of prominent color and use representative vectors from these extracted regions in the image indices. This way we end up with a much smaller index which does not have the granularity of a histogram. Instead similarity is based on our vector angular distance measure between a query color vector and the indexed representative vectors.

关键词： color vectors angular measure color exclusion gamma nonlinearity

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