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conference on storage and retrieval for image and video databases II

作者： OAKLEY, J DAVIS, D SHANN, R XYDEAS, C UNIV MANCHESTER MULTI MEDIA RES GRPMANCHESTER M13 9PLLANCSENGLAND

ISBN: (纸本)0819414808

The Manchester Content Addressable image Database (CAID) is a generic tool which has been designed for image informatics and computer vision problems. The system stores pre- computed feature tokens, which are obtained by conventional processing of the input images, into a database which is accessed by a specialized query language (MVQL). MVQL extends the usual notion of a query language to include creation and refinement of groupings based on the stored attributes of the pre-computed features, and these groupings can be continued in a nested fashion. The aim of this paper is to report on two recent application studies. The first study concerns the automatic registration of volume MR data sets. This is achieved entirely within the CAID environment (i.e., as a database query) using only a short MVQL specification. The method used is based on curve token correspondence and an exhaustive search of transformation space. Some results on the estimated accuracy of the result will be included. The second application is concerned with the classification of microfossil images into morphological groups. Preliminary work on detecting microfossil structures was reported in Shann et al. Here we address the problem of classifying detected structures into six broad morphological groups. This is achieved using MVQL to define `structure' measures from the distribution of curve tokens in a circular region around each microfossil. The results are surprisingly good considering the very limited feature evidence used. Both application studies confirm the general applicability of the CAID structure and its query language.

关键词： Sensors databases Head image registration Magnetic resonance imaging image classification image segmentation Sensor performance image processing image retrieval

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Intelligent video editing system using a neural network coding scheme

Intelligent video editing system using a neural network codi...

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storage and retrieval for image and video databases iii

作者： Rickman, Richard M. Stonham, T.John Brunel Univ. Uxbridge Middx UK

ISBN: (纸本)081941767X

video editors are frequently required to access sections of a video sequence which contain a particular scene. This may be regarded as an image retrieval-by-content problem where the user wishes to select images from within a large database according to a measure of similarity to a target. We present an intelligent video editing system based on a neural network coding scheme. The transformation learnt by the neural network maps each image into a very compact index which supports rapid fuzzy matching of video images. The neural network is trained using a learning law which produces an information preserving transform. Trained in this way, the node learns features which characterize the distribution of scenes within the video sequence. Each image frame in the sequence is coded with respect to these features. We show how the system performs on a typical sequence of newsreel footage and discuss the factors affecting the performance of both the training and the retrieval mechanism.

关键词： video signal processing

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Comparative study of strategies for illumination-invariant texture representations

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Proceedings of SPIE - The International Society for Optical Engineering 1999年 3656卷 653-664页

作者： Levienaise-Obadia, B. Kittler, J. Christmas, W. Univ of Surrey Guildford United Kingdom

Illumination invariance is of paramount importance to annotate video sequences stored in large videodatabases consistently. Yet, popular texture analysis methods such as multichannel filtering techniques do not yield illumination-invariant texture representations. In this paper, we assess the effectiveness of three illumination normalisation schemes for texture representations derived from Gabor filter outputs. The schemes aim at overcoming intensity scaling effects due to changes in ilumination conditions. A theoretical analysis and experimental results enable us to select one scheme as the most promising one. In this scheme, a normalising factor is derived at each pixel by combining the energy responses of different filters at that pixel. The scheme overcomes illumination variations well, while still preserving discriminatory textural information. Further statistical analysis may shed light on other interesting properties or limitations of the scheme.

关键词： image analysis

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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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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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video segmentation in the wavelet domain

Video segmentation in the wavelet domain

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conference on Multimedia storage and Archiving Systems iii

作者： Mandal, MK Panchanathan, S Univ Ottawa Sch Informat Technol & Engn Ottawa ON K1N 6N5 Canada

ISBN: (纸本)0819429880

Automatic video indexing is an important feature in the design of a video databases. Recently, compressed domain techniques have become popular due their inherent advantages of efficiency and reduced complexity. Wavelet transform is emerging as a powerful tool for efficient compression of visual information. A variety of wavelet based video compression techniques have been reported in the literature. However, there has been little work done in the area of video indexing in the wavelet domain. In this paper, we present video segmentation techniques in a wavelet based compression framework. These techniques employ wavelet coefficients, their distribution, and the motion vectors estimated by the associated video coder. Simulation result shows that the proposed techniques provide a good indexing performance at a low complexity.

关键词： video segmentation indexing content-based retrieval wavelets motion vectors

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Fast video segmentation using encoding cost data

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Proceedings of SPIE - The International Society for Optical Engineering 1999年 3656卷 699-709页

作者： De Queiroz, Ricardo L. Bozdagi, Gozde Sencar, Taha Xerox Corp Webster United States

This paper presents a simple and effective pre-processing method developed for the segmentation of MPEG compressed video sequences. The proposed method for scene-cut detection only involves computing the number of bits spent for each frame (encoding cost data), thus avoiding decoding the bitstream. The information is separated into I-, P-, B-frames, thus forming 3 vectors which are independently processed by a new peak detection algorithm based on overcomplete filter banks and on joint thresholding using a confidence number. Each processed vector yields a set of candidate frame numbers, i.e. 'hints' of positions where scene-cuts may have occurred. The 'hints' for all frame types are recombined into one frame sequence and clustered into scene cuts. The algorithm was not designed to distintuish among types of cuts but rather to indicate its position and duration. Experimental results show that the proposed algorithm is effective in detecting abrupt scene changes as well as gradual transitions. For precision demanding applications, the algorithm can be used with a low confidence factor just to select the frames that are worth being investigated by a more complex algorithm. The algorithm is not particularly tailored to MPEG and can be applied to most video compression techniques.

关键词： image segmentation

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Watermark embedded DCT indexing keys for portable imaging devices

Watermark embedded DCT indexing keys for portable imaging de...

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21st Annual International conference on Consumer Electronics (ICCE)

作者： Armstrong, A Jiang, J Univ Glamorgan Sch Comp Pontypridd CF37 1DL M Glam Wales

ISBN: (纸本)0780373006

The maintenance required on modern media databases to allow efficient indexing and retrieval is becoming an ever-increasing burden. An explosion in the content of the internet [1], the lowering in costs associated with imaging devices and the digital revolution have placed much higher requirements on the storage of graphics and video, both in commercial domains and at home. Fully automated indexing systems will be very desirable to manage and organise these large amounts of data. We tackle the problem of image indexing in the compressed domain using a Neural Network extraction technique together with a DCT domain watermark. This approach allows the indexing of the image entirely in the DCT domain, thus benefits from substantial computational savings. Coupled with DCT based watermarking, the technique allows for the real-time embedding of indexing data in popular image (JPEG) and video (MPEG) formats. Such a low-cost combination (both in processing and key storage) makes the method highly suitable for the use in portable imaging devices such as digital cameras were it would be highly desirable to have some means of indexing the images they have stored.

关键词： image retrieval

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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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Content-based image retrieval via distributed databases

Content-based image retrieval via distributed databases

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2008 International conference on image and video retrieval, CIVR 2008

作者： Jarrah, Kambiz Guan, Ling Ryerson Multimedia Research Laboratory Department of Electrical and Computer Engineering Ryerson University Toronto ON Canada Canada Research Chair Department of Electrical and Computer Engineering Ryerson University Toronto ON Canada

ISBN: (纸本)9781605580708

The overall objective of this paper is to present an extended application of Content-Based image retrieval (CBIR) over distributed (decentralized) image databases. Traditional image retrieval system design has implicitly relied on a local (centralized) query server, such as IBM's QBIC[1], Columbia's VisualSEEk[2], MIT's PhotoBook [3], and UCSD's Viagemtrade;[4]. With the growing popularity of the internet, however, the focus of the research in this area has been shifted toward content query over distributed databases. Ng et al.[5] has studied a peer-clustering model for the query with the assumption that the image collection at each peer node falls under one category. Even though, this assumption is effective for preliminary studies, it is unable to implant the practical end-user behaviors. Lee et al.[6] has introduced a novel approach to study practical scenarios where multiple image categories exist in each individual database in the distributed storage network. This approach is proven to be an effective method to improve retrieval precision via identifying the community neighborhood who shares similar content collection. The main focus of this paper is to study behavior of a CBIR engine in an interactive distributed environment. In the proposed approach, the query image is sent to all registered databases in the network. Response of each database is then collected and transferred to a local server where a supervised relevance identification approach is applied to identify final outcome of the search. Response of each database is quantified via estimating the statistical resemblance of top image candidates to the existing query image. Comprehensive experiments demonstrate feasibility of the proposed methodology. Copyright 2008 ACM.

关键词： Search engines

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