Segmentation of Textured Images by Pyramid Linking

  • Bradley P. Kjell
  • Charles R. Dyer
Part of the NATO ASI Series book series (volume 25)

Abstract

A pyramid linking algorithm for texture segmentation is presented. It is based on the computation of spatial properties of long, straight edge segments at fixed orientations. Features are computed for each edge segment in terms of the distances to the nearest neighboring edge segments of given orientations. This produces a set of sparse “edge separation maps” of features which are then used as the basis of a pyramid linking procedure for hierarchically grouping edges into homogeneously textured regions. Segmentation is performed in one bottom-up pass of linking nodes to their most similar parent. Results are shown using both the raw and smoothed edge separation features. All of the steps of the procedure can be efficiently implemented as parallel operations on a pyramid machine.

Keywords

Explosive Pyramid 

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References

  1. [1]
    A. Rosenfeld, Ed., Multiresolution Image Processing and Analysis. Berlin, West Germany: Springer-Verlag, 1984.MATHGoogle Scholar
  2. [2]
    B. P. Kjell and C. R. Dyer, “Edge separation and orientation texture measures,” Proc. IEEE Conf. Computer Vision and Pattern Recognition, San Francisco, C A, June 1985, pp. 306–311.Google Scholar
  3. [3]
    B. P. Kjell, “Edge separation and orientation texture measures,” Ph.D. dissertation, Computer Science Department, University of Wisconsin, Madison, WI, 1985.Google Scholar
  4. [4]
    T. Phillips and T. Matsuyama, The labeled discrete Voronoi diagram, Technical Report TR-1278, Center for Automation Research, University of Maryland, College Park, MD, May 1983.Google Scholar
  5. [5]
    P. C. Chen and T. Pavlidis, “Segmentation by texture using a co-occurrence matrix and a split-and-merge algorithm,” Computer Graphics and Image Processing, vol. 10, pp. 172–182, 1979.CrossRefGoogle Scholar
  6. [6]
    M. Pietikainen and A. Rosenfeld, “Image segmentation by texture using pyramid node linking,” IEEE Trans. Syst., Man, Cybern., vol. SMC-11, pp. 822–825, 1981.Google Scholar
  7. [7]
    K. I. Laws, “Texture energy measures,” Proc. Image Understanding Workshop, Los Angeles, CA, Nov. 1979, pp. 47–51.Google Scholar
  8. [8]
    P. J. Burt, T. H. Hong, and A. Rosenfeld, “Segmentation and estimation of image region properties through cooperative hierarchical computation,” IEEE Trans. Syst., Man, Cybern., vol. SMC-11, pp. 802–809, 1981.Google Scholar
  9. [9]
    J. Cibulskis and C. R. Dyer, “Node linking strategies in pyramids for image segmentation,” IEEE Trans. Syst., Man, Cybern., vol. SMC-14, pp. 424–436, 1984.Google Scholar
  10. [10]
    P. J. Burt, “The pyramid as a structure for efficient computation,” in Multiresolution Image Processing and Analysis, A. Rosenfeld, Ed. Berlin, West Germany: Springer- Verlag, 1984, pp. 6–35.Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 1986

Authors and Affiliations

  • Bradley P. Kjell
    • 1
  • Charles R. Dyer
    • 2
  1. 1.Computer and Information Science DepartmentGeorge Mason UniversityFairfaxUSA
  2. 2.Computer Science DepartmentUniversity of WisconsinMadisonUSA

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