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Chinese Cursive Script Character Image Retrieval Based on an Integrated Probability Function

  • Irwin King
  • Zhong Jin
  • David Yuk-Ming Chan
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 1929)

Abstract

Often in content-based image retrieval, a single image at- tribute may not have enough discriminative information for retrieval. On the other hand, when multiple features are used, it is hard to determine the suitable weighting factors for various features for optimal retrieval. In this paper, we present an idea of integrated probability function and use it to combine features for Chinese cursive script character image retrieval. A database of 1400 monochromatic images is used. Experimental results show that the proposed system based on Legendre moment feature, Zernike moment feature, and pseudo Zernike moment feature is robust to retrieval deformed images. Using our integrated probability function, ninety-nine percent of the targets are ranked at the top 2 positions.

Keywords

Image Retrieval Combination Scheme Zernike Moment Image Retrieval System Large Scale Database 
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

  • Irwin King
    • 1
  • Zhong Jin
    • 2
  • David Yuk-Ming Chan
    • 1
  1. 1.Department of Computer Science and EngineeringThe Chinese University of Hong KongShatinHong Kong
  2. 2.Department of Computer ScienceNanjing University of Science and TechnologyNanjingPeople’s Republic of China

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