Abstract
The watershed transform is considered as the most appropriate method for image segmentation in the field of mathematical morphology. In the following paper, we present an adapted topological watershed algorithm suited for a rapid and effective implementation on Shared Memory Parallel Machine (SMPM). The introduced algorithm allows a parallel watershed computing while preserving the given topology. No prior minima extraction is needed, nor the use of any sorting step or hierarchical queue. The strategy that guides the parallel watershed computing, labeled SDM-Strategy (equivalent to Split-Distributes and Merge), is also presented. Experimental analyses such as execution time, performance enhancement, cache consumption, efficiency and scalability are also presented and discussed.
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