Work

Parallel N-Dimensional Exact Signed Euclidean Distance Transform

Year: 2006

Type: article

Abstract: 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.

Source: The Insight Journal

DOI: 10.54294/ogv879

Authors: Robert Staubs, Andriy Fedorov, Leonidas Linardakis, Benjamin Dunton, Nikos Chrisochoides

Language: English

Topic: Digital Image Processing Techniques

Subfield: Computer Vision and Pattern Recognition

Field: Computer Science

Domain: Physical Sciences

Open Access status: hybrid

OpenAlex ID: W4205445980

FWCI:

Cites: 2

Cited by: 3

Related to: 10