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Leaf Image Retrieval with Shape Features

  • Zhiyong Wang
  • Zheru Chi
  • Dagan Feng
  • Qing Wang
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 1929)

Abstract

In this paper we present an eficient two-step approach of using a shape characterization function called centroid-contour distance curve and the object eccentricity (or elongation) for leaf image retrieval. Both the centroid-contour distance curve and the eccentricity of a leaf image are scale, rotation, and translation invariant after proper normalizations. In the frist step, the eccentricity is used to rank leaf images, and the top scored images are further ranked using the centroid-contour distance curve together with the eccentricity in the second step. A thinningbased method is used to locate start point(s) for reducing the matching time. Experimental results show that our approach can achieve good performance with a reasonable computational complexity.

Keywords

Centroid-contour distance Shape representation Content-based image retrieval Leaf image processing 

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References

  1. 1.
    A. K. Jain. Fundamentals of Digital Image Processing. Prentice Hall, London, UK, 1989.Google Scholar
  2. 2.
    BV. M. Mehtre, M. S. Kankanhalli, and W. F. Lee. Shape measures for content based image retrieval: a comparison. Information Processing & Management, 33(3), 1997.Google Scholar
  3. 3.
    Xianfeng Ding, Weixing Kong, Changbo Hu, and Songde Ma. Image retrieval using schwarz representation of one-dimensional feature. In Visual Information and Information Systems, pages 443–450, Amsterdam, The Netherlands, June 1999.Google Scholar
  4. 4.
    C.W. Richard and H. Hemami. Identification of three-dimensional objects using Fourier descriptors of the boundary curve. IEEE TRANS. on Systems, Man and Cybernetics, SMC-4(4), July 1974.Google Scholar
  5. 5.
    S. A. Dudani, K. J. Breeding, and R. B. McGhee. Aicraft identification by moment invariants. IEEE TRANS. on Computers, C-26(1), Jan. 1977.Google Scholar
  6. 6.
    E. Persoon and K. S. Fu. Shape discrimination using Fourier description. IEEE TRANS. on Systems, Man And Cybernetics, SMC-7(3), Mar. 1977.Google Scholar
  7. 7.
    C. Chen. Improved moment invariants for shape discrimination. Pattern Recognition, 26(5), 1993.Google Scholar
  8. 8.
    A.K. Jain and A. Vailaya. Image retrieval using color and shape. Pattern Recognition, 29(8), 1996.Google Scholar
  9. 9.
    A.K. Jain and A. Vailaya. Shape-based retrieval:a case study with trademark image database. Pattern Recognition, 31(9), 1998.Google Scholar
  10. 10.
    R. Egas, N. Huijsmans, M. Lew, and N. Sebe. Adapting k-d trees to visual retrieval. In Visual Information and Information Systems, pages 533–540, Amsterdam, The Netherlands, June 1999.Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2000

Authors and Affiliations

  • Zhiyong Wang
    • 1
  • Zheru Chi
    • 1
  • Dagan Feng
    • 1
  • Qing Wang
    • 1
  1. 1.Center for Multimedia Signal Processing Department of Electronic and Information EngineeringThe Hong Kong Polytechnic UniversityHung Hom, KowloonHong Kong

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