Advertisement

Texture Segmentation by Fuzzy Clustering of Spatial Patterns

  • Yong Xia
  • Rongchun Zhao
  • Yanning Zhang
  • Jian Sun
  • Dagan Feng
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4223)

Abstract

An approach to perceptual segmentation of textured images by fuzzy clustering of spatial patterns is proposed in this paper. The dissimilarity between a texture feature, which is modeled as a spatial pattern, and each cluster is calculated as a combination of the Euclidean distance in the feature space and the spatial dissimilarity, which reflects how much of the pattern’s neighborhood is occupied by other clusters. The proposed algorithm has been applied to the segmentation of texture mosaics. The results of comparative experiments demonstrate that the proposed approach can segment textured images more effectively and provide more robust segmentations.

Keywords

Fuzzy Cluster Synthetic Aperture Radar Texture Image Markov Random Field Texture Segmentation 
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.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Reed, T.R., Hans du Buf, J.M.: A Review of Recent Texture Segmentation and Feature Extraction Techniques. CVGIP: Image Understanding 57(3), 359–372 (1993)CrossRefGoogle Scholar
  2. 2.
    Krishnapuram, R., Freg, C.P.: Fitting an Unknown Number of Lines and Planes to Image Data through Compatible Cluster Merging. Pattern Recogn. 25, 385–400 (1992)CrossRefGoogle Scholar
  3. 3.
    Deng, H., Clausi, D.A.: Unsupervised Segmentation of Synthetic Aperture Radar Sea Ice Imagery Using a Novel Markov Random Field Model. IEEE Trans. Geosci. Remote Sensing 43, 528–538 (2005)CrossRefGoogle Scholar
  4. 4.
    Liew, A.W.C., Leung, S.H., Lau, W.H.: Segmentation of Color Lip Images by Spatial Fuzzy Clustering. IEEE Trans. Fuzzy Systems 11, 542–549 (2003)CrossRefGoogle Scholar
  5. 5.
    Brodatz, P.: Texture: A Photographic Album for Artists and Designers. Dover, New York (1966)Google Scholar
  6. 6.
    Bezdek, J.C.: Pattern Recognition with Fuzzy Objective Function Algorithms. Plenum Press, New York (1981)MATHGoogle Scholar
  7. 7.
    Manjunath, B.S., Chellappa, R.: Unsupervised Texture Segmentation Using Markov Random Fields. IEEE Trans. Pattern Anal. Machine Intell. 13, 478–482 (1991)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Yong Xia
    • 1
    • 3
  • Rongchun Zhao
    • 1
  • Yanning Zhang
    • 1
  • Jian Sun
    • 2
  • Dagan Feng
    • 3
    • 4
  1. 1.School of ComputerNorthwestern Polytechnical UniversityXi’anChina
  2. 2.School of Automatic ControlNorthwestern Polytechnical UniversityXi’anChina
  3. 3.School of Information Technologies, F09University of SydneyAustralia
  4. 4.Dept. of Electronic and Information EngineeringHong Kong Polytechnic University 

Personalised recommendations