Further Optimized Parallel Algorithm of Watershed Segmentation Based on Boundary Components Graph

  • Haifang Zhou
  • Xuejun Yang
  • Yu Tang
  • Nong Xiao
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3222)

Abstract

Watershed segmentation/transform is a classical method for image segmentation in gray scale mathematical morphology. Nevertheless watershed algorithm has strong recursive nature, so straightforward parallel one has a very low efficiency. Firstly, the advantages and disadvantages of some existing parallel algorithms are analyzed. Then, a Further Optimized Parallel Watershed Algorithm (FOPWA) is presented based on boundary components graph. As the experiments show, FOPWA optimizes both running time and relative speedup, and has more flexibility.

Keywords

Parallel Algorithm Defense Technology Lower Distance Boundary Pixel Relative Speedup 
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.

References

  1. 1.
    Meijster, A., Roerdink, J.B.T.M.: A proposal for the implementation of a parallel water-shed algorithm. In: Hlavac, V., Sara, R. (eds.) Computer Analysis of Images and Patterns, pp. 790–795. New York (1995)Google Scholar
  2. 2.
    Zhou, H.F., Jiang, Y.H., Yang, X.J.: An Improved Parallel Watershed Algorithm for Distributed Memory System. In: Zhou, W.L. (ed.) Proceedings of the 5th International Conference on Algorithms and Architecture for Parallel Processing, pp. 310–314. IEEE Computer Society, Los Alamitos (2002)Google Scholar
  3. 3.
    Zhou, H.F., Jiang, Y.H., Yang, X.J.: Researches on serial and parallel strategies of water-shed transform. Journal of national university of defense technology 24(6), 71–76 (2002)Google Scholar
  4. 4.
    Moga, A.N., Viero, T., Dobrin, B.P.: Implementation of a distributed watershed algorithm. In: Serra, J., Soille, P. (eds.) Computational Imaging and Vision Mathematical Morphology and Its Applications to Image Processing, Dordrecht, the Netherlands, pp. 281–288 (1994)Google Scholar
  5. 5.
    Moga, A.N., Viero, T., Gabbouj, M., et al.: Parallel watershed algorithm based on sequen-tial scannings. In: Pitas, I. (ed.) Proceedings 1995 IEEE Workshop on Nonlinear Signal and Image Processing, Greece. Neos Marmaras, vol. II, pp. 991–994 (1995)Google Scholar
  6. 6.
    Cramariuc, B., Gabbouj, M.: A parallel watershed algorithm based on rain falling simula-tion. In: Proceedings 12th European Conference on Circuit Theory and Design, Istanbul, Turkey, vol. 1, pp. 339–342 (1995)Google Scholar

Copyright information

© IFIP International Federation for Information Processing 2004

Authors and Affiliations

  • Haifang Zhou
    • 1
  • Xuejun Yang
    • 1
  • Yu Tang
    • 2
  • Nong Xiao
    • 1
  1. 1.Institute of ComputerNational University of Defense TechnologyChangshaChina
  2. 2.Institute of Electronic TechnologyNational University of Defense TechnologyChina

Personalised recommendations