Skip to main content
Log in

A Fast Parallel Algorithm for Convex Hull Problem of Multi-Leveled Images

  • Published:
Journal of Intelligent and Robotic Systems Aims and scope Submit manuscript

Abstract

In this paper, we propose a parallel algorithm to solve the convex hull problem for an (n×n) multi-leveled image using a reconfigurable mesh connected computer of the same size as a computational model. The algorithm determines parallely the convex hull of all the connected components of the multileveled image. It is based on some geometric properties and a top-down strategy. The complexity of the algorithm is O(log n) times. Using some approximations on the component contours, this complexity is reduced to O(log m) times where m is the number of the vertices of the convex hull of the biggest component of the image.This complexity is reached thanks to the polymorphic properties of the mesh where all the components are simultaneously and separately processed.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Similar content being viewed by others

References

  1. Elmesbahi, J. and Charkaoui, J.: Structure analysis for Gray level pictures on a mesh connected computer, in: Proc. of IEEE Internat. Conf. on SMC, October 1986, pp. 1415–1419.

  2. Fu, A. M. N. and Yan, H.: Effective classification of planar shapes based on curve segment properties, Pattern Recognition Lett. 18 (1997), 55–61.

    Google Scholar 

  3. Hayachi, T. et al.: An O((log log n) 2 ) time algorithm to compute the convex hull of sorted points on reconfigurable meshes, IEEE Trans. Parallel Distributed Systems 9(12) (1998).

  4. Jarvis, C.: Fitting polygons to figure boundary data, Austral. Comput. J. 3 (1971), 50–54.

    Google Scholar 

  5. Kim, C. E. and Stojmenović, I.: Parallel algorithms for digital geometry, CS-87-179, Washington State University, Pullman, December 1987.

  6. Li, H. and Maresca, M.: Polymorphic torus architecture for computer vision, IEEE Trans. Pattern Anal. Mach. Intelligence 11(3) (1989), 233–242.

    Google Scholar 

  7. Ling, T. et al.: Efficient parallel processing of image contours, IEEE Trans. Pattern Anal.Mach. Intelligence 15(1) (1993), 69–81.

    Google Scholar 

  8. Miller, R. et al.: Geometric algorithms for digitized pictures on a mesh connected computer, IEEE Trans. Pattern Anal. Mach. Intelligence 7(2) (1985).

  9. Miller, R. et al.: Meshes with reconfigurable buses, in: Proc. of the 5th MIT Conf. on Advanced Research in VLSI, Cambridge, MA, 1988, pp. 163–178.

  10. Miller, R., Prasanna-Kummar, V. K., Reisis, D. I. and Stout, Q. F.: Parallel computation on reconfigurable meshes, IEEE Trans. Comput. 42(6) (1993), 678–692.

    Google Scholar 

  11. Miller, R. and Stout, Q. F.:Mesh computer algorithms for computational geometry, IEEE Trans. Comput. 38(3) (1989), 321–340.

    Google Scholar 

  12. Prasanna, V. K. and Reisis, D. I.: Image computation on meshes with multiple broadcast, IEEE Trans. Pattern Anal. Mach. Intelligence 11(11) (1989), 1194–1201.

    Google Scholar 

  13. Stout, Q. F.: Mapping vision algorithms to parallel architectures, Proc. IEEE (August 1988).

Download references

Author information

Authors and Affiliations

Authors

Rights and permissions

Reprints and permissions

About this article

Cite this article

Bouattane, O., Elmesbahi, J. & Rami, A. A Fast Parallel Algorithm for Convex Hull Problem of Multi-Leveled Images. Journal of Intelligent and Robotic Systems 33, 285–299 (2002). https://doi.org/10.1023/A:1015083706590

Download citation

  • Issue Date:

  • DOI: https://doi.org/10.1023/A:1015083706590

Navigation