Hierarchical image segmentation using the watershed algorithm with a streaming implementation [electronic resource] /
Abstract (Summary)
We have implemented a graphical user interface (GUI) based semi-automatic hierarchical
segmentation scheme, which works in three stages. In the first stage, we process the original
image by filtering and threshold the gradient to reduce the level of noise. In the second
stage, we compute the watershed segmentation of the image using the rainfalling simulation
approach. In the third stage, we apply two region merging schemes, namely implicit region
merging and seeded region merging, to the result of the watershed algorithm. Both the region
merging schemes are based on the watershed depth of regions and serve to reduce the
oversegmentation produced by the watershed algorithm. Implicit region merging automatically
produces a hierarchy of regions. In seeded region merging, a selected seed region can be grown
from the watershed result, producing a hierarchy. A meaningful segmentation can be simply
chosen from the hierarchy produced.
We have also proposed and tested a streaming algorithm based on the watershed algorithm,
which computes the segmentation of an image without iterative processing of adjacent blocks.
We have proved that the streaming algorithm produces the same result as the serial watershed
algorithm. We have also discussed the extensibility of the streaming algorithm to efficient
parallel implementations.
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Bibliographical Information:
Advisor:
School:The University of Tennessee at Chattanooga
School Location:USA - Tennessee
Source Type:Master's Thesis
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