6 August 1993 Systolic array for complete Euclidean distance transform
Author Affiliations +
Proceedings Volume 2064, Machine Vision Applications, Architectures, and Systems Integration II; (1993) https://doi.org/10.1117/12.150277
Event: Optical Tools for Manufacturing and Advanced Automation, 1993, Boston, MA, United States
Abstract
The Euclidean distance transform (EDT) converts a binary image into one where each pixel has a value equal to the Euclidean distance to the nearest foreground pixel. It has important uses in image analysis, computer vision and robotics, and so its VLSI implementation is very useful. In this paper, a sequential algorithm which does not require global operations is first presented. We then present a square and a triangular shaped systolic arrays to realize the algorithm. For a n X n image on an equal size systolic array, the computing time is 5n- 5.
© (1993) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Ling Chen and Henry Y.H. Chuang "Systolic array for complete Euclidean distance transform", Proc. SPIE 2064, Machine Vision Applications, Architectures, and Systems Integration II, (6 August 1993); doi: 10.1117/12.150277; https://doi.org/10.1117/12.150277
PROCEEDINGS
7 PAGES


SHARE
Advertisement
Advertisement
RELATED CONTENT

Space And Time Requirements For Two Image Data Structures
Proceedings of SPIE (March 26 1989)
Graphical Operations In A Hierarchical Parallel Computer
Proceedings of SPIE (January 16 1985)
The Use Of Systolic Arrays In Robot Vision
Proceedings of SPIE (June 08 1986)
Grey-level encoding of openings and closings
Proceedings of SPIE (November 30 1993)
Texture Based Image Analysis With Neural Nets
Proceedings of SPIE (February 28 1990)
Trajectory Planning In Time Varying Environments, 1 TPP =...
Proceedings of SPIE (January 16 1985)

Back to Top