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Parallel image component labelling with watershed transformation

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2 Author(s)
A. N. Moga ; Signal Process. Lab., Tampere Univ. of Technol., Finland ; M. Gabbouj

The parallel watershed transformation used in gray scale image segmentation is reconsidered on the basis of the component labeling problem. The main idea is to break the sequentiality of the watershed transformation and to correctly delimit the extent of all connected components locally, on each processor, simultaneously. The internal fragmentation of the catchment basins, due to domain decomposition, into smaller subcomponents is finally solved by employing a global connected components operator. Therefore, in a pyramidal structure of master-slave processors, internal contours of adjacent subcomponents within the same component are hierarchically removed. Global final connected areas are efficiently obtained in log2 N steps on a logical grid of N processors. Timings and segmentation results of the algorithm built on top of the message passing interface and tested on the Gray T3D are brought forward to justify the superiority of the novel design solution compared against previous implementations

Published in:

IEEE Transactions on Pattern Analysis and Machine Intelligence  (Volume:19 ,  Issue: 5 )