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
New: Prefer using the following doi: https://doi.org/10.54294/ogv879
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.