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Concurrent Computation of Attribute Filters on Shared Memory Parallel Machines

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5 Author(s)
Wilkinson, M.H.F. ; Inst. for Math. & Comput. Sci., Univ. of Groningen, Groningen ; Hui Gao ; Hesselink, W.H. ; Jonker, J.-E.
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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.

Published in:

Pattern Analysis and Machine Intelligence, IEEE Transactions on  (Volume:30 ,  Issue: 10 )

Date of Publication:

Oct. 2008

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