Abstract
The paper proposes a new parallel connected-component-tree construction algorithm based on line independent building and progressive merging of partial 1-D trees. Two parallelization strategies were developed: the parallelism maximization strategy, which balances the workload of the processes, and the communication minimization strategy, which minimizes communication among the processes. The new algorithm is able to process any pixel data type, thanks to not using a hierarchical queue. The algorithm needs only the input and output buffers and a small stack. A speedup of 3.57 compared to the sequential algorithm was obtained on Opteron 4-core shared memory ccNUMA architecture. Performance comparison with existing state of the art is also discussed.
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Matas, P. et al. (2008). Parallel Algorithm for Concurrent Computation of Connected Component Tree. In: Blanc-Talon, J., Bourennane, S., Philips, W., Popescu, D., Scheunders, P. (eds) Advanced Concepts for Intelligent Vision Systems. ACIVS 2008. Lecture Notes in Computer Science, vol 5259. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-88458-3_21
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DOI: https://doi.org/10.1007/978-3-540-88458-3_21
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-88457-6
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