Table of Contents Author Guidelines Submit a Manuscript
International Journal of Reconfigurable Computing
Volume 2011, Article ID 712494, 10 pages
Research Article

A Genetic Programming Approach to Reconfigure a Morphological Image Processing Architecture

1Computer Science Department, Federal University of São Carlos, Rodovia Washington Luís, km 235, 13565-905 São Carlos, SP, Brazil
2Department of Electrical Engineering, University of São Paulo, Avenida Trabalhador São Carlense, 400 13566-590 São Carlos SP, Brazil

Received 20 May 2010; Accepted 10 September 2010

Academic Editor: Elías Todorovich

Copyright © 2011 Emerson Carlos Pedrino et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Linked References

  1. E. R. Dougherty, Ed., An Introduction to Morphological Image Processing, SPIE, Bellingham, Wash, USA, 1992.
  2. J. Serra, Image Analysis and Mathematical Morphology, Academic Press, San Diego, Calif, USA, 1982.
  3. A. R. Weeks Jr., Fundamentals of Electronic Image Processing, SPIE, Bellingham, Wash, USA, 1996.
  4. P. Soille, Morphological Image Analysis, Principles and Applications, Springer, Berlin, Germany, 1999.
  5. M. Sonka, V. Hlavac, and R. Boyle, Image Processing, Analysis and Machine Vision, Chapman & Hall, Boca Raton, Fla, USA, 1993.
  6. J. Facon, Morfologia Matemática: Teoria e Exemplos, Editora Universitária da Pontifícia Universidade Católica do Paraná, Prado Velho, Brazil, 1996.
  7. F. Ortiz, F. Torres, E. De Juan, and N. Cuenca, “Colour mathematical morphology for neural image analysis,” Real-Time Imaging, vol. 8, no. 6, pp. 455–465, 2002. View at Google Scholar · View at Scopus
  8. P. Maragos, “Lattice image processing: a unification of morphological and fuzzy algebraic systems,” Journal of Mathematical Imaging and Vision, vol. 22, no. 2, pp. 333–353, 2005. View at Publisher · View at Google Scholar · View at Scopus
  9. C. R. Giardina and E. R. Dougherty, Morphological Methods in Image and Signal Processing, Prentice-Hall, Englewood Cliffs, NJ, USA, 1988.
  10. R. M. Haralick, S. R. Sternberg, and X. Zhuang, “Image analysis using mathematical morphology,” IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 9, no. 4, pp. 532–550, 1987. View at Google Scholar · View at Scopus
  11. J. Angulo and J. Serra, Morphological Coding of Color Images by Vector Connected Filters, Centre de Morphologie Mathématique, Ecole des Mines de Paris, Paris, France, 2005.
  12. J. Chanussot and P. Lambert, “Total ordering based on space filling curves for multivalued morphology,” in Proceedings of the 4th International Symposium on Mathematical Morphology and Its Applications, pp. 51–58, 1998.
  13. S. Marshall, N. R. Harvey, and D. Greenhalgh, “Design of morphological filters using genetic algorithms,” in Proceedings of the 10th International Signal Processing Conference (EUSIPCO '00), Tampere, Finland, 2000.
  14. M. I. Quintana, R. Poli, and E. Claridge, “Genetic programming for mathematical mor-phology algorithm design on binary images,” in Proceedings of the International Conference of Knowledge Based Computer Systems (KBCS '02), pp. 161–171, 2002.
  15. J. Barrera, E. R. Dougherty, and N. S. Tomita, “Automatic programming of binary morphological machines by design of statistically optimal operators in the context of computational learning theory,” Journal of Electronic Imaging, vol. 6, no. 1, pp. 54–67, 1997. View at Google Scholar · View at Scopus
  16. E. R. Dougherty and R. P. Loce, Eficient Design Strategies for the Optimal Binary Digital Morphological Filter: Probabilities, Constraints, and Structuring Element Libraries, Marcel Dekker, New York, NY, USA, 1993.
  17. M. Schmitt, “Mathematical morphology and artificial intelligence: an automatic programming system,” Signal Processing, vol. 16, no. 4, pp. 389–401, 1989. View at Google Scholar · View at Scopus
  18. J. Barrera, R. Terada, R. Hirata Jr., and N. S. T. Hirata, “Automatic programming of morphological machines by PAC learning,” Fundamenta Informaticae, vol. 41, no. 1-2, pp. 229–258, 2000. View at Google Scholar · View at Scopus
  19. M. Yu, N. Eua-anant, A. Saudagar, and L. Udpa, “Genetic algorithm approach to image segmentation using morphological operations,” in Proceedings of the International Conference on Image Processing, pp. 775–779, 1998.
  20. I. Yoda, K. Yamamoto, and H. Yamada, “Automatic acquisition of hierarchical mathematical morphology procedures by genetic algorithms,” Image and Vision Computing, vol. 17, no. 10, pp. 749–760, 1999. View at Publisher · View at Google Scholar
  21. J. Bala and H. Wechsler, “Shape analysis using morphological processing and genetic Algorithms,” in Proceedings of the IEEE International Conference on Tools with Artificial Intelligence (TAI '91), pp. 130–137, Los Alamitos, Calif, USA, 1991.
  22. N. R. Harvey and S. Marshall, “The use of genetic algorithms in morphological filter design,” Signal Processing: Image Communication, vol. 8, no. 1, pp. 55–71, 1996. View at Publisher · View at Google Scholar
  23. M. I. Quintana Hernandez, Genetic programming applied to morphological image processing, Ph.D. thesis, School of Computer Science, University of Birmingham, 2005.
  24. D. Barrios, A. Carrascal, D. Manrique, and J. Ríos, “Optimisation with real-coded genetic algorithms based on mathematical morphology,” International Journal of Computer Mathematics, vol. 80, no. 3, pp. 275–293, 2003. View at Publisher · View at Google Scholar · View at Scopus
  25. D. Barrios, D. Manrique, and J. Porras, “Real-coded genetic algorithms based on ma-thematical morphology,” Advances in Pattern Recognition, vol. 1876/2000, pp. 706–715, 2000. View at Publisher · View at Google Scholar
  26. T. Belpaeme, “Evolution of visual feature detectors,” in Proceedings of the 1st European Workshop on Evolutionary Computation in Image Analysis and Signal Processing (EvoISAP '99), R. Poli, S. Cagnoni, H. M. Voigt, T. Fogarty, and P. Nordin, Eds., pp. 1–10, Goteborg, Sweden, 1999.
  27. J. Holland, Adaptation in Natural and Artificial Systems, MIT Press, Cambridge, Mass, USA, 1975.
  28. J. Koza, Genetic Programming, MIT Press, Cambridge, Mass, USA, 1992.
  29. GP FAQ, 2002,
  30. M. Bhattacharya, A. Abraham, and B. Nath, “A linear genetic programming approach for modeling electricity demand prediction in victoria,” in Proceedings of the hybrid information systems (HIS '01), pp. 379–393, 2001.
  31. M. Oltean, C. Groşan, and M. Oltean, “Encoding multiple solutions in a linear genetic programming chromosome,” in International Conference on Computational Science, pp. 1281–1288, 2004.
  32. D. Goldberg and K. Déb, “A comparative analysis of selection schemes used in genetic algorithms,” in Foundations of Genetic Algorithms, G. Rawlins, Ed., pp. 69–93, Morgan Kauffmann, Boston, Mass, USA, 1991. View at Google Scholar
  33. Altera, 2008,
  34. E. C. Pedrino and V. O. Roda, “Pipeline architecture for real time morphological color image processing,” in Proceedings of the 2nd Southern Conference on Programmable Logic, Mar Del Plata, Argentina, Fpga Based Systems, Escuela Politécnica Superior, Universidad Autónoma de Madrid, Madrid, Spain, 2006.
  35. E. C. Pedrino, J. H. Saito, and V. O. Roda, “Architecture for binary mathematical mor-phology reconfigurable by genetic programming,” in Proceedings of the 6th Southern Conference on Programmable Logic, Universidade Federal de Pernambuco, Porto de Galinhas, Brasil, 2010.
  36. E. C. Pedrino and V. O. Roda, “Real-time morphological pipeline architecture using high-capacity programmable logical devices,” Journal of Electronic Imaging, vol. 16, no. 2, Article ID 023002, 2007. View at Publisher · View at Google Scholar · View at Scopus