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Proceedings Paper

Systolic array for complete Euclidean distance transform
Author(s): Ling Chen; Henry Y.H. Chuang
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Paper 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.

Paper Details

Date Published: 6 August 1993
PDF: 7 pages
Proc. SPIE 2064, Machine Vision Applications, Architectures, and Systems Integration II, (6 August 1993); doi: 10.1117/12.150277
Show Author Affiliations
Ling Chen, Univ. of Pittsburgh (United States)
Henry Y.H. Chuang, Univ. of Pittsburgh (United States)

Published in SPIE Proceedings Vol. 2064:
Machine Vision Applications, Architectures, and Systems Integration II
Bruce G. Batchelor; Susan Snell Solomon; Frederick M. Waltz, Editor(s)

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