The Euclidean distance transform (EDT) is an operation to convert a binary image consisting of black and white pixels to a representation where each pixel has the Euclidean distance of the nearest black pixel. The EDT has many applications in computer vision and image processing. In this paper, we p
Reconfigurable Mesh Algorithms for the Hough Transform
โ Scribed by J.F. Jenq; S. Sahni
- Publisher
- Elsevier Science
- Year
- 1994
- Tongue
- English
- Weight
- 675 KB
- Volume
- 20
- Category
- Article
- ISSN
- 0743-7315
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โฆ Synopsis
We develop parallel algorithms to compute the Hough transform on a reconfigurable mesh with buses (RMESH) multiprocessor. The (p) angle Hough transform of an (N \times N) image can be computed in (O(p \log (N / p))) time by an (N \times N) RMESH, in (O((p /) (N) ) (\log N) ) time by an (N \times N^{2}) RMESH with (N) copies of the image pretiled, in (O((p / \sqrt{N}) \log N)) time by an (N^{1.5} \times N^{1.5}) RMESH, and in (O((p / N) \log N)) time by an (N^{2} \times N^{2}) RMESH. 01994 Academic Press, Inc.
๐ SIMILAR VOLUMES
model the propagation delay on a bus-unit 1 by a constant, and to only permit the class of algorithms, denoted by A k , which configure bus components bound in size to at most k bus-units to run on the model. We give a detailed description of our reconfigurable mesh model in the following section.
A novel reconfigurable network referred to as the Reconfigurable Multi-Ring Network (RMRN) is described. The RMRN is shown to be a truly scalable network, in that each node in the network has a fixed degree of connectivity and the reconfiguration mechanism ensures a network diameter of \(O\left(\log