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Pattern Analysis and Machine Intelligence, IEEE Transactions on

Issue 8 • Date Aug. 1996

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Displaying Results 1 - 10 of 10
  • Introduction to the Special Section on Digital Libraries: Representation and Retrieval [Guest Editor

    Publication Year: 1996
    Cited by:  Papers (5)
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    Freely Available from IEEE
  • A parallel computing approach to creating engineering concept spaces for semantic retrieval: the Illinois Digital Library Initiative project

    Publication Year: 1996 , Page(s): 771 - 782
    Cited by:  Papers (30)  |  Patents (2)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1472 KB)  

    This research presents preliminary results generated from the semantic retrieval research component of the Illinois Digital Library Initiative (DLI) project. Using a variation of the automatic thesaurus generation techniques, to which we refer to as the concept space approach, we aimed to create graphs of domain-specific concepts (terms) and their weighted co-occurrence relationships for all major engineering domains. Merging these concept spaces and providing traversal paths across different concept spaces could potentially help alleviate the vocabulary (difference) problem evident in large-scale information retrieval. In order to address the scalability issue related to large-scale information retrieval and analysis for the current Illinois DLI project, we conducted experiments using the concept space approach on parallel supercomputers. Our test collection included computer science and electrical engineering abstracts extracted from the INSPEC database. The concept space approach called for extensive textual and statistical analysis (a form of knowledge discovery) based on automatic indexing and co-occurrence analysis algorithms, both previously tested in the biology domain. Initial testing results using a 512-node CM-5 and a 16-processor SGI Power Challenge were promising View full abstract»

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  • Automating image processing for scientific data analysis of a large image database

    Publication Year: 1996 , Page(s): 854 - 859
    Cited by:  Papers (17)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (792 KB)  

    Describes the Multimission VICAR Planner (MVP): an AI planning system which uses knowledge about image processing steps and their requirements to construct executable image processing scripts to support high-level science requests made to the Jet Propulsion Laboratory (JPL) Multimission Image Processing Subsystem (MIPS). This article describes a general AI planning approach to automation and application of the approach to a specific area of image processing for planetary science applications involving radiometric correction, color triplet reconstruction, and mosaicing in which the MVP system significantly reduces the amount of effort required by image processing experts to fill a typical request View full abstract»

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  • MARCO: MAp retrieval by COntent

    Publication Year: 1996 , Page(s): 783 - 798
    Cited by:  Papers (18)  |  Patents (5)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1732 KB)  

    A system named MARCO (denoting map retrieval by content) that is used for the acquisition, storage, indexing, and retrieval of map images is presented. The input to MARCO are raster images of separate map layers and raster images of map composites. A legend-driven map interpretation system converts map layer images from their physical representation to their logical representation. This logical representation is then used to automatically index both the composite and the layer images. Methods for incorporating logical and physical layer images as well as composite images into the framework of a relational database management system are described. Indices are constructed on both the contextual and the spatial data thereby enabling efficient retrieval of layer and composite images based on contextual as well as spatial specifications. Example queries and query processing strategies using these indices are described. The user interface is demonstrated via the execution of an example query. Results of an experimental study on a large amount of data are presented. The system is evaluated in terms of accuracy and in terms of query execution time View full abstract»

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  • Texture features for browsing and retrieval of image data

    Publication Year: 1996 , Page(s): 837 - 842
    Cited by:  Papers (1047)  |  Patents (58)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (956 KB)  

    Image content based retrieval is emerging as an important research area with application to digital libraries and multimedia databases. The focus of this paper is on the image processing aspects and in particular using texture information for browsing and retrieval of large image data. We propose the use of Gabor wavelet features for texture analysis and provide a comprehensive experimental evaluation. Comparisons with other multiresolution texture features using the Brodatz texture database indicate that the Gabor features provide the best pattern retrieval accuracy. An application to browsing large air photos is illustrated View full abstract»

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  • A real-time matching system for large fingerprint databases

    Publication Year: 1996 , Page(s): 799 - 813
    Cited by:  Papers (174)  |  Patents (92)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (2016 KB)  

    With the current rapid growth in multimedia technology, there is an imminent need for efficient techniques to search and query large image databases. Because of their unique and peculiar needs, image databases cannot be treated in a similar fashion to other types of digital libraries. The contextual dependencies present in images, and the complex nature of two-dimensional image data make the representation issues more difficult for image databases. An invariant representation of an image is still an open research issue. For these reasons, it is difficult to find a universal content-based retrieval technique. Current approaches based on shape, texture, and color for indexing image databases have met with limited success. Further, these techniques have not been adequately tested in the presence of noise and distortions. A given application domain offers stronger constraints for improving the retrieval performance. Fingerprint databases are characterized by their large size as well as noisy and distorted query images. Distortions are very common in fingerprint images due to elasticity of the skin. In this paper, a method of indexing large fingerprint image databases is presented. The approach integrates a number of domain-specific high-level features such as pattern class and ridge density at higher levels of the search. At the lowest level, it incorporates elastic structural feature-based matching for indexing the database. With a multilevel indexing approach, we have been able to reduce the search space. The search engine has also been implemented on Splash 2-a field programmable gate array (FPGA)-based array processor to obtain near-ASIC level speed of matching. Our approach has been tested on a locally collected test data and on NIST-9, a large fingerprint database available in the public domain View full abstract»

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  • Using discriminant eigenfeatures for image retrieval

    Publication Year: 1996 , Page(s): 831 - 836
    Cited by:  Papers (526)  |  Patents (11)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1216 KB)  

    This paper describes the automatic selection of features from an image training set using the theories of multidimensional discriminant analysis and the associated optimal linear projection. We demonstrate the effectiveness of these most discriminating features for view-based class retrieval from a large database of widely varying real-world objects presented as “well-framed” views, and compare it with that of the principal component analysis View full abstract»

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  • Compact representations of videos through dominant and multiple motion estimation

    Publication Year: 1996 , Page(s): 814 - 830
    Cited by:  Papers (122)  |  Patents (17)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (2980 KB)  

    An explosion of on-line image and video data in digital form is already well underway. With the exponential rise in interactive information exploration and dissemination through the World-Wide Web (WWW), the major inhibitors of rapid access to on-line video data are costs and management of capture and storage, lack of real-time delivery, and nonavailability of content-based intelligent search and indexing techniques. The solutions for capture, storage, and delivery may be on the horizon or a little beyond. However, even with rapid delivery, the lack of efficient authoring and querying tools for visual content-based indexing may still inhibit as widespread a use of video information as that of text and traditional tabular data is currently. In order to be able to nonlinearly browse and index into videos through visual content, it is necessary to develop authoring tools that can automatically separate moving objects and significant components of the scene, and represent these in a compact form. Given that video data comes in torrents-almost a megabyte every 30th of a second-it will be highly inefficient to search for objects and scenes in every frame of a video. In this paper, we present techniques to automatically derive compact representations of scenes and objects from the motion information. Image motion is a significant cue in videos for the separation of scenes into their significant components and for the separation of moving objects. Motion analysis is useful in capturing the visual content of videos for indexing and browsing in two different ways. First, separation of the static scene from moving objects can be accomplished by employing dominant 2D/3D motion estimation methods. Alternatively, if the goal is to be able to represent the fixed scene too as a composition of significant structures and objects, then simultaneous multiple motion methods might be more appropriate. In either case, view-based summarized representations of the scene can be created by video compositing/mosaicing based on the estimated motions. We present robust algorithms for both kinds of representations: 1) dominant motion estimation based techniques which exploit a fairly common occurrence in videos that a mostly fixed background (scene) is imaged with or without independently moving objects, and 2) simultaneous multiple motion estimation and representation of motion video using layered representations. Ample examples of the representations achieved by each method are included in the paper View full abstract»

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  • Exploiting the JPEG compression scheme for image retrieval

    Publication Year: 1996 , Page(s): 849 - 853
    Cited by:  Papers (42)  |  Patents (4)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (720 KB)  

    We address the problem of retrieving images from a large database using an image as a query. The method is specifically aimed at databases that store images in JPEG format, and works in the compressed domain to create index keys. A key is generated for each image in the database and is matched with the key generated for the query image. The keys are independent of the size of the image. Images that have similar keys are assumed to be similar, but there is no semantic meaning to the similarity View full abstract»

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  • Retrieving multispectral satellite images using physics-based invariant representations

    Publication Year: 1996 , Page(s): 842 - 848
    Cited by:  Papers (19)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1872 KB)  

    We present a set of algorithms and a search strategy for the robust content-based retrieval of multispectral satellite images. Since the property of interest in these images is usually the physical characteristics of ground cover, we use representations and methods that are invariant to illumination and atmospheric conditions. The representations and algorithms are derived for this application from a physical model for the formation of multispectral satellite images. The use of several representations and algorithms is necessary to interpret the diversity of physical and geometric structure in these images. Algorithms are used that exploit multispectral distributions, multispectral spatial structure, and labeled classes. The performance of the system is demonstrated on a large set of multispectral satellite images taken over different areas of the United States under different illumination and atmospheric conditions View full abstract»

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Aims & Scope

The IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI) is published monthly. Its editorial board strives to present most important research results in areas within TPAMI's scope.

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Editor-in-Chief
David A. Forsyth
University of Illinois