Gowri Allampalli-Nagaraj

University of Washington Tacoma, Tacoma, Washington, United States

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Publications (2)2.21 Total impact

  • Gowri Allampalli-Nagaraj · Isabelle Bichindaritz
    [Show abstract] [Hide abstract]
    ABSTRACT: This paper presents a system implemented to evaluate the retrieval efficiency of images when they are semantically indexed using a combination of a web ontology language and the low-level features of the image. Finding a similarity measure algorithm to retrieve images based on the semantic metadata can be very challenging due to diverse image content and inadequate domain-specific ontologies describing the content. The existing methods for indexing images are primarily based on text. While these methods are widely used due to their simplicity, they are not very efficient as they require a domain expert and the textual interpretations of image content vary from person to person. In our approach, we leverage sophisticated image-processing techniques to automatically extract image content information into MPEG-7 format and associate them to the existing domain ontologies developed by experts, thereby, bridging the gap between low-level features and high-level semantics. This implementation and validation experiments show that a high retrieval accuracy rate is obtained when all the image descriptors are combined with an ontology while building the semantic metadata for indexing images.
    No preview · Article · Feb 2009 · Engineering Applications of Artificial Intelligence
  • Gowri Allampalli-Nagaraj · Isabelle Bichindaritz

    No preview · Conference Paper · Jan 2007

Publication Stats

13 Citations
2.21 Total Impact Points


  • 2009
    • University of Washington Tacoma
      • Institute of Technology
      Tacoma, Washington, United States