SIMPLIcity: Semantics-sensitive Integrated Matching for Picture LIbraries

  • James Z. Wang
  • Jia Li
  • Gio Wiederholdy
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 1929)


We present here SIMPLIcity (Semantics-sensitive Integrated Matching for Picture LIbraries), an image retrieval system using semantics classification and integrated region matching (IRM) based upon image segmentation. The SIMPLIcity system represents an image by a set of regions, roughly corresponding to objects, which are characterized by color, texture, shape, and location. The system classifies images into categories which are intended to distinguish semantically meaningful differences, such as textured versus nontextured, indoor versus outdoor, and graph versus photograph. Retrieval is enhanced by narrowing down the searching range in a database to a particular category and exploiting semantically-adaptive searching methods. A measure for the overall similarity between images, the IRM distance, is defined by a region-matching scheme that integrates properties of all the regions in the images. This overall similarity approach reduces the adverse effect of inaccurate segmentation, helps to clarify the semantics of a particular region, and enables a simple querying interface for region-based image retrieval systems. The application of SIMPLIcity to a database of about 200,000 general-purpose images demonstrates accurate retrieval at high speed. The system is also robust to image alterations.


Image Database Color Histogram Semantic Type Matched Image Classi Cation 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2000

Authors and Affiliations

  • James Z. Wang
    • 1
    • 2
  • Jia Li
    • 1
    • 3
  • Gio Wiederholdy
    • 1
    • 4
  1. 1.Dept. of Computer ScienceStanford UniversityStanfordUSA
  2. 2.Biomedical InformaticsStanford UniversityStanford
  3. 3.Xerox Palo Alto Research CenterStanford
  4. 4.Biomedical InformaticsStanford UniversityStanford

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