
Parallel N-Dimensional Exact Signed Euclidean Distance Transform
Please use this identifier to cite or link to this publication: http://hdl.handle.net/1926/307 |
Published in The Insight Journal - 2006 July - December.
Submitted by Robert Staubs on 09-16-2006.
The computation speed for distance transforms becomes important in a wide variety of image processing applications. Current ITK library filters do not see any benefit from a multithreading environment. We introduce a three-dimensional signed parallel implementation of the exact Euclidean distance transform algorithm developed by Maurer et al. with a theoretical complexity of O(n/p) for n voxels and p threads. Through this parallelization and efficient use of data structures we obtain approximately 3
times mean speedup on standard tests on a 4-processor machine compared with the current ITK exact Euclidean distance transform filter.
times mean speedup on standard tests on a 4-processor machine compared with the current ITK exact Euclidean distance transform filter.
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Categories: | Programming, Programming |
Keywords: | Euclidean distance transform, parallel distance transform, distance transform |
Toolkits: | ITK, CMake |
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