CSDL Home IEEE Transactions on Pattern Analysis & Machine Intelligence 2008 vol.30 Issue No.10 - October

Subscribe

Issue No.10 - October (2008 vol.30)

pp: 1800-1813

ABSTRACT

Morphological attribute filters have not previously been parallelized, mainly because they are both global and non-separable. We propose a parallel algorithm which achieves efficient parallelism for a large class of attribute filters, including attribute openings, closings, thinnings and thickenings, based on Salembier's Max-Trees and Min-trees. The image or volume is first partitioned in multiple slices. We then compute the Max-trees of each slice using any sequential Max-Tree algorithm. Subsequently, the Max-trees of the slices can be merged to obtain the Max-tree of the image. A C-implementation yielded good speed-ups on both a 16-processor MIPS 14000 parallel machine, and a dual-core Opteron-based machine. It is shown that the speed-up of the parallel algorithm is a direct measure of the gain with respect to the sequential algorithm used. Furthermore, the concurrent algorithm shows a speed gain of up to 72% on a single-core processor, due to reduced cache thrashing.

INDEX TERMS

Filtering, Enhancement Parallel algorithms, mathematical morphology, connected filters

CITATION

Michael H.F. Wilkinson, Hui Gao, Wim H. Hesselink, Jan-Eppo Jonker, Arnold Meijster, "Concurrent Computation of Attribute Filters on Shared Memory Parallel Machines",

*IEEE Transactions on Pattern Analysis & Machine Intelligence*, vol.30, no. 10, pp. 1800-1813, October 2008, doi:10.1109/TPAMI.2007.70836REFERENCES

- [3] A. Meijster, J.B.T.M. Roerdink, and W.H. Hesselink, “A General Algorithm for Computing Distance Transforms in Linear Time,”
Proc. Int'l Symp. Math. Morphology (ISMM '00), pp. 331-340, June 2000.- [4] P. Salembier and J. Serra, “Flat Zones Filtering, Connected Operators, and Filters by Reconstruction,”
IEEE Trans. Image Processing, vol. 4, pp. 1153-1160, 1995.- [7] J.C. Klein, “Conception et Réalisation d'une Unité Logique Pour l'analyse Quantitative d'images,” PhD dissertation, Nancy Univ., 1976.
- [8] L. Vincent, “Morphological Grayscale Reconstruction in Image Analysis: Application and Efficient Algorithm,”
IEEE Trans. Image Processing, vol. 2, pp. 176-201, 1993.- [10] L. Vincent, “Morphological Area Openings and Closings for Grey-Scale Images,”
Proc. NATO Shape in Picture Workshop: Math. Description of Shape in Grey-Level Images, Y.-L. O, A. Toet, D. Foster, H.J.A.M. Heijmans, and P. Meer, eds., pp. 197-208, 1993.- [11] P. Salembier, A. Oliveras, and L. Garrido, “Anti-Extensive Connected Operators for Image and Sequence Processing,”
IEEE Trans. Image Processing, vol. 7, pp. 555-570, 1998.- [12] E.R. Urbach and M.H.F. Wilkinson, “Shape-Only Granulometries and Grey-Scale Shape Filters,”
Proc. Int'l Symp. Math. Morphology (ISMM '02), pp. 305-314, 2002.- [14] M.H.F. Wilkinson and M.A. Westenberg, “Shape Preserving Filament Enhancement Filtering,”
Proc. Medical Image Computing and Computer-Assisted Intervention (MICCAI '01), W.J. Niessen and M.A. Viergever, eds., pp. 770-777, 2001.- [20] J. Roubal and T.K. Peucker, “Automated Contour Labeling and the Contour Tree,”
Proc. Int'l Symp. Computer-Assisted Cartography (AUTOCARTO '85), pp. 472-481, 1985.- [21] M. van Kreveld, R. van Oostrum, C. Bajaj, V. Pascucci, and D. Schikore, “Contour Trees and Small Seed Sets for Iso-Surface Traversal,”
Proc. 13th Ann. Symp. Computational Geometry, pp. 212-220, 1997.- [22] H. Carr, J. Snoeyink, and U. Axen, “Computing Contour Trees in All Dimensions,”
Computational Geometry, vol. 24, pp. 75-94, 2003.- [24] P. Monasse and F. Guichard, “Fast Computation of a Contrast Invariant Image Representation,”
IEEE Trans. Image Processing, vol. 9, pp. 860-872, 2000.- [25] G. Bertrand, “On Topological Watersheds,”
J. Math. Imaging and Vision, vol. 22, pp. 217-230, 2005.- [27] U. Braga-Neto and J. Goutsias, “A Theoretical Tour of Connectivity in Image Processing and Analysis,”
J. Math. Imaging and Vision, vol. 19, pp. 5-31, 2003.- [28] J. Serra, “Connectivity on Complete Lattices,”
J. Math. Imaging and Vision, vol. 9, pp. 231-251, 1998.- [31] C. Berger, T. Geraud, R. Levillain, N. Widynski, A. Baillard, and E. Bertin, “Effective Component Tree Computation with Application to Pattern Recognition in Astronomical Imaging,”
Proc. Int'l Conf. Image Processing, Sept. 2007.- [33] B.A. Galler and M.J. Fischer, “An Improved Equivalence Algorithm,”
Comm. ACM, vol. 7, pp. 301-303, 1964.- [36] M.K. Hu, “Visual Pattern Recognition by Moment Invariants,”
IRE Trans. Information Theory, vol. 8, pp. 179-187, 1962.- [38] G.K. Ouzounis and M.H.F. Wilkinson, “Mask-Based Second Generation Connectivity and Attribute Filters,”
IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 29, pp. 990-1004, 2007.- [39] G.K. Ouzounis and M.H.F. Wilkinson, “A Parallel Dual-Input Max-Tree Algorithm for Shared Memory Machines,”
Proc. Int'l Symp. Math. Morphology (ISMM '07), pp. 449-460, 2007. |