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2nd International conference on Geometric Modeling and Imaging

作者： Li, Ze-Nian Simon Fraser Univ Sch Comp Sci Burnaby BC V5A 1S6 Canada

ISBN: (纸本)9780769529011

Search based on image contents is an important issue in large image and video databases. In this paper two methods for a better content-based image retrieval (CBIR) are presented, namely the use of recognition kernel and locales. Features of model objects are extracted at levels that are most appropriate to yield only, the necessary yet sufficient details, together they form the kernel. Instead of relying on image segmentation, a method of feature localization based on locales is developed. It is shown that the deployment of the recognition kernel and locales in a pyramidal (multiresolution) framework delivers good retrieval results.

关键词： Content based retrieval

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A beowulf class parallel remote sensed image database retrieval system developed in ASSIST environment

A beowulf class parallel remote sensed image database retrie...

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conference on storage and retrieval Methods and Applications for Multimedia 2005

作者： Di Lecce, v Guerriero, A Guarino, I Politecn Bari I-70121 Bari Italy

ISBN: (纸本)0819456551

image databases are now currently utilized in a wide range of different areas, in particular, the development and application of remote sensing platforms result in the production of huge amounts of image data. One of the major problem in the practical implementation of a Content-based image retrieval (CBIR) for remotely sensed images is that the content-based indexing and searching process always requires extremely high computational power. On the other hand, the content-based image retrieval algorithms are very suitable for parallel computation as the algorithms can be broken into several data independent processes for running on a parallel computer. In this paper, we discuss the porting problem of a sequential application of remote sensed image retrieval in a parallel environment using the new paradigm of programming introduced by the birth of a new structured program languages (Assist 1.2) and compared performances to sequential and to commercial multiprocessors solutions.

关键词： Parallel Programming ASSIST skeleton remote sensed image Database sorting image Features.

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Content-based image object retrieval by scale-space representation of shapes

Content-based image object retrieval by scale-space represen...

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conference on Multimedia storage and Archiving Systems III

作者： Hoffman, ME Wong, EK Polytech Univ Dept Comp & Informat Sci Brooklyn NY 11201 USA

ISBN: (纸本)0819429880

vast amounts of inexpensive storage and cost-effective input devices have promoted a rapid increase in the amount of stored digital images and video. Retrieving desired images from databases is a challenging problem, not easily solved by existing database methods. Shape is one popular feature used to automate retrieval of images by content. Example shape features include the Fourier descriptor for describing shape boundaries, and area or compactness for describing shape regions, among others. We present a new shape-representation method based on extracting an image surface ridge-line called the Most Prominent Ridge-Line (MPRL) in scale-space. The MPRL is extracted by minimizing the second spatial derivative orthogonal to the ridge-line direction. The scale of the MPRL point is proportional to the image object's width. Matching query and database image MPRLs is shown to be an effective method for retrieving images based on shape. A unique feature of the proposed method is that the scale dimension may be weighted to allow for any desired amount of shape details in image retrieval.

关键词： image database content-based image retrieval shape representation coarseness scale-space image pyramid topography ridge-line

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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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Multi modal semantic indexing for image retrieval 10

Multi modal semantic indexing for image retrieval

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ACM International conference on image and video retrieval, ACM-CIvR 2010

作者： Chandrika, Pulla Jawahar, C.v. CVIT International Institute of Information Technology Hyderabad-500 032 India

ISBN: (纸本)9781450301176

Popular image retrieval schemes generally rely only on a single mode, (either low level visual features or embedded text) for searching in multimedia databases. Many popular image collections (eg. those emerging over Internet) have associated tags, often for human consumption. A natural extension is to combine information from multiple modes for enhancing effectiveness in retrieval. In this paper, we propose two techniques: Multi-modal Latent Semantic Indexing (MMLSI) and Multi-Modal Probabilistic Latent Semantic Analysis (MMpLSA). These methods are obtained by directly extending their traditional single mode counter parts. Both these methods incorporate visual features and tags by generating simultaneous semantic contexts. The experimental results demonstrate an improved accuracy over other single and multi-modal methods. Copyright © 2010 ACM.

关键词： image retrieval

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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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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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Content-based image retrieval in the world-wide-web - A web-agent for fetching portraits 5

Content-based image retrieval in the world-wide-web - A web-...

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storage and retrieval for image and video databases v 1997

作者： Munkelt, Olaf Kaufmann, Oliver Eckstein, Wolfgang Orleansstr. 34 München81667 Germany Technische Universität München Institut für Informatik Forschungsgruppe Bildverstehen Orleansstr. 34 München81667 Germany

This article propose a way to automatically retrieve images from the world-wide-web using a semantic description for images and an agent concept for the retrieval of images. The system represents image in a textual way, e.g. look for a portrait of the a specific person, or fetch an image showing a countryside in Southern California. This textual descriptions are fed in search machines, e.g. yahoo, alta-vista. The resulting html documents are seeked for links. The next step subsequently processes each link by fetching the document other the net, converting it to an ascii representation, and performing a full text search by using the image description. This leads to starting points of images which are retrieved via a web-agent. The image descriptions are decomposed in a set of parts containing image operations which are further processed, e.g. a set for representing the background of a portrait tries to find a homogeneous region in the image because this is likely to find in a portrait. Additional operations are performed on the foregroud, i.e. the image region which contains e.g. the face of a person. The system is realized using two C++ libraries: one for buildung up web-agents, LIWA++, and one for processing images, HORUS. © 1997 SPIE. All rights reserved.

关键词： image analysis

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Texture content based retrieval using text descriptions

Texture content based retrieval using text descriptions

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7th storage and retrieval for image and video databases conference

作者： Kuan, JKP Joyce, DW Lewis, PH ADC Metr Dev Grp Richmond TW9 1BN Surrey England

ISBN: (纸本)0819431273

We developed a content based retrieval scheme for texture by using text based description. The texture technique is based on our previous work which uses very simple texture primitives such as edges and plain regions to generate features. Other methods that apply complicated statistics can be difficult to transcribe into understandable forms for normal users. Unlike these other methods, with the simplicity of our features, we can express them in terms of simple language. Hence we can bridge the gap between semantics and computed features. A number of benefits can be achieved which opens a new horizon for content based retrieval with texture. For example, the user can request a texture image without necessarily knowing what types of textures are stored. In this paper we describe the method of translating such features and the partial weighted Euclidean distance matching which allows users to describe only the parts that they are interested in. This allows them to gradually refine their texture descriptions.

关键词： texture content based retrieval semantics language

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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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