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Journal of Optical Technology

| SIMULTANEOUS RUSSIAN-ENGLISH PUBLICATION

  • Vol. 79, Iss. 11 — Nov. 1, 2012
  • pp: 693–697

Wavelet segmentation of color texture images

V. T. Fisenko and T. Yu. Fisenko  »View Author Affiliations


Journal of Optical Technology, Vol. 79, Issue 11, pp. 693-697 (2012)
http://dx.doi.org/10.1364/JOT.79.000693


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Abstract

This paper discusses methods of segmenting complex texture images. A method of multiscale wavelet segmentation of color textures has been developed, based on their characteristic attributes and chromaticity characteristics. Multiscale image analysis is used to form the texture attributes. The method makes it possible to combine estimates of the texture characteristics on the basis of the discrete wavelet transformation and the color characteristics of the texture. Estimates of the segmentation efficiency are obtained from the number of iterations of the wavelet transformation, the type of wavelet basis, the form of the color-coordinate space, and the size of the filtering window for estimating the segmentation attributes.

© 2012 OSA

History
Original Manuscript: May 29, 2012
Published: November 30, 2012

Citation
V. T. Fisenko and T. Yu. Fisenko, "Wavelet segmentation of color texture images," J. Opt. Technol. 79, 693-697 (2012)
http://www.opticsinfobase.org/jot/abstract.cfm?URI=jot-79-11-693


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References

  1. V. T. Fisenko and T. Yu. Fisenko, “Segmentation of color texture images,” in International Conference, Applied Optics, Collection of Papers, Vol. 3, St. Petersburg, 2008, pp. 359–363.
  2. V. T. Fisenko and T. Yu. Fisenko, Computer Processing and Image Recognition. A Textbook (SPbGU ITMO, St. Petersburg, 2008).
  3. R. M. Haralick, “Statistical and structural approaches to texture,” Proc. IEEE 67, 786 (1979). [CrossRef]
  4. S. Malla, Wavelets in Signal Processing (Mir, Moscow, 2005).
  5. A. V. Leonenkov, Fuzzy Modelling in the matlab and fuzzytech medium (BKhV-Peterburg, St. Petersburg, 2005).
  6. V. T. Fisenko and T. Yu. Fisenko, “Method of automatically analyzing color images,” Opt. Zh. 70, No. 9, 18 (2003). [J. Opt. Technol. 70, 637 (2003)].
  7. B. Manjunath, J.-R. Ohm, V. Vasudevan, and A. Yamada, “Color and texture descriptors,” IEEE Trans. Circuits Syst. Video Technol. 11, 703 (2001). [CrossRef]
  8. P. Brodatz, A Photographic Album for Artists and Designers (Dover, New York, 1966).
  9. Vision Texture (electronic resource), http://vismod.media.mit.edu/vismod/imagery/VisionTexture/vistex.html (2012).
  10. University of Oulu texture database (electronic resource), http://www.outex.oulu.fi (2012).

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