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Fast recursive grayscale morphology operators: from the algorithm to the pipeline architecture

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Abstract

This paper presents a new algorithm for efficient computation of morphological operations for gray images and the specific hardware. The method is based on a new recursive morphological decomposition method of 8-convex structuring elements by only causal two-pixel structuring elements (2PSE). Whatever the element size, erosion or/and dilation can then be performed during a unique raster-like image scan involving a fixed reduced analysis neighborhood. The resulting process offers low computation complexity combined with easy description of the element form. The dedicated hardware is generic and fully regular, built from elementary interconnected stages. It has been synthesized into an FPGA and achieves high-frequency performances for any shape and size of structuring element.

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References

  1. Boltyanskii, V.G., Soltan, P.S.: Combinatorial geometry and convexity classes. Russian Mathematical Surveys 33(1), 1–45 (1978)

    Article  Google Scholar 

  2. Chen, S., Haralick, R.: Recursive erosion, dilation, opening, and closing transforms. IEEE Trans. Image Process. 4(3), 335–345 (1995)

    Article  Google Scholar 

  3. Chien, S., Ma, S., Chen, L.: Partial-result-reuse architecture and its design technique for morphological operations with flat structuring elements. IEEE Trans. Circuits Syst. Video Technol. 15(9), 1156–1169 (2005)

    Article  Google Scholar 

  4. Clienti, C., Bilodeau, M., Beucher, S.: An efficient hardware architecture without line memories for morphological image processing. In: ACIVS ’08: Proceedings of the 10th International Conference on Advanced Concepts for Intelligent Vision Systems, pp. 147–156 (2008)

  5. Coltuc, D., Pitas, I.: Fast computation of a class of running filters. IEEE Trans. Signal. Process. 46(6), 549–553 (1998)

    Article  Google Scholar 

  6. Diamantaras, K., Kung, S.: A linear systolic array for real-time morphological image processing. J. VLSI Signal Process. 17, 43–55 (1997)

    Article  MATH  Google Scholar 

  7. Eckhardt, U.: Digital lines and digital convexity. Digital Image Geom. 2243, 209–228 (2001)

    Article  MathSciNet  Google Scholar 

  8. Gil, J., Kimmel, R.: Efficient dilation, erosion, opening, and closing algorithms. IEEE Pattern Anal. Mach. Intell. 24(12), 1607–1617 (2002)

    Article  Google Scholar 

  9. Ji, L., Piper, J., Tang, J.: Erosion and dilation of binary images by arbitrary structuring elements using interval coding. Pattern Recogn. Lett. (9), 201–249 (1989)

    Google Scholar 

  10. Normand, N.: Convex structuring element decomposition for single scan binary mathematical morphology. In: Conference on Discrete Geometry for Computer Imagery, Naples (2003)

  11. Ong, S., Sunwoo, M.: A new cost-effective morphological filter chip. In: IEEE Workshop Design Signal Processing Systems, pp. 421–430 (1997)

  12. Pitas, I.: Fast aglorithms for running ordering and max/min calculation. IEEE Trans. Circuits Syst. 36(6), 795–804 (1989)

    Article  Google Scholar 

  13. Ruetz, P., Brodersen, R.: Architectures and design techniques for real-time image processing IC'S. IEEE J. Solid State Circuit 22(2), 233–250 (1987)

    Article  Google Scholar 

  14. Serra, J.: IImage Analysis and Mathematical Morphology. Academic Press, London (1982)

    MATH  Google Scholar 

  15. Sheu, M., Wang, J., Chen, J., Suen, A., Jeang, Y., Lee, J.: A data-reuse architecture for gray-scale morphologic operations. IEEE Trans. Circuits on Syst II, Analog Digital Signal Process 39(10), 753–756 (1992)

    Article  MATH  Google Scholar 

  16. Soille, P., Breen, E.J., Jones, R.: Recursive implementation of erosions and dilations along discrete lines at arbitrary angles. IEEE Pattern Anal. Mach. Intell. 18(5), 562–567 (1996)

    Google Scholar 

  17. Van Herk, M.: A fast algorithm for local minimum and maximum filters on rectangular and octagonal kernels. Pattern Recogn. Lett. 13(7), 517–521 (1992)

    Google Scholar 

  18. Wang, X., Bertrand, G.: An algorithm for a generalized distance transformation based on minkowski operations. In: 9th International Conference on Pattern Recognition, pp. 1164–1168 (1988)

  19. Xu, J.: Decomposition of convex polygonal morphological structuring elements into neighborhoods subsets. IEEE Trans. Pattern Anal. Mach. Intell. 13(2), 153–162 (1991)

    Article  Google Scholar 

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Authors and Affiliations

  1. UMR CNRS 6164 IETR, INSA Rennes, 20 av. des Buttes de Coesmes, 35043, Rennes, France

    Olivier Déforges & Marie Babel

  2. UMR CNRS 6597 IRCCYN, Ecole Polytechnique Nantes, La Chantrerie, BP 60601, 44306, Nantes, France

    Nicolas Normand

Authors
  1. Olivier Déforges
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  2. Nicolas Normand
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  3. Marie Babel
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Correspondence to Olivier Déforges.

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Déforges, O., Normand, N. & Babel, M. Fast recursive grayscale morphology operators: from the algorithm to the pipeline architecture. J Real-Time Image Proc 8, 143–152 (2013). https://doi.org/10.1007/s11554-010-0171-8

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  • DOI: https://doi.org/10.1007/s11554-010-0171-8

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