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    Creating a Large-Scale Content-Based Airphoto Image Digital Library

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    Author
    Zhu, Bin
    Ramsey, Marshall C.
    Chen, Hsinchun
    Issue Date
    2000-01
    Submitted date
    2004-08-13
    Keywords
    Evaluation
    Digital Libraries
    Local subject classification
    National Science Digital Library
    NSDL
    Artificial intelligence lab
    AI lab
    Content-based image retrieval
    Digital library
    Gabor wavelets
    Self-organizing map
    System evaluation
    
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    Citation
    Creating a Large-Scale Content-Based Airphoto Image Digital Library 2000-01, 9(1):163-167 IEEE TRANSACTIONS ON IMAGE PROCESSING
    Publisher
    IEEE
    Journal
    IEEE TRANSACTIONS ON IMAGE PROCESSING
    Description
    Artificial Intelligence Lab, Department of MIS, University of Arizona
    URI
    http://hdl.handle.net/10150/105813
    Abstract
    This paper describes a content-based image retrieval digital library that supports geographical image retrieval over a testbed of 800 aerial photographs, each 25 megabytes in size. In addition, this paper also introduces a methodology to evaluate the performance of the algorithms in the prototype system. The major contributions of this paper are two. 1) We suggest an approach that incorporates various image processing techniques including Gabor filters, image enhancement, and image compression, as well as information analysis technique such as self-organizing map (SOM) into an effective large-scale geographical image retrieval system. 2) We present two experiments that evaluate the performance of the Gaborfilter- extracted features along with the corresponding similarity measure against that of human perception, addressing the lack of studies in assessing the consistency between an image representation algorithm or an image categorization method and human mental model.
    Type
    Journal Article (Paginated)
    Language
    en
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