DocumentCode :
2438228
Title :
Exploiting task and data parallelism in parallel Hough and Radon transforms
Author :
Krishnaswamy, Dilip ; Banerjee, Prithviraj
Author_Institution :
Center for Reliable & High Performance Comput., Illinois Univ., Urbana, IL, USA
fYear :
1997
fDate :
11-15 Aug 1997
Firstpage :
441
Lastpage :
444
Abstract :
Edge detection and shape detection in digital images are very computationally intensive problems. Parallel algorithms can potentially provide significant speedups while preserving the quality of the result obtained. Hough and Radon Transforms are projection-based transforms which are commonly used for edge detection and shape detection respectively. We propose in this paper various new parallel algorithms which exploit both task and data parallelism available in Hough and Radon transforms algorithms. A memory scalable aggressive task parallel algorithm is shown to be the most optimal algorithm in terms of memory scalability and performance on an IBM SP2
Keywords :
Hough transforms; Radon transforms; edge detection; parallel algorithms; performance evaluation; Hough transforms; IBM SP2; Radon transforms; computationally intensive problems; data parallelism; digital images; edge detection; memory scalability; memory scalable aggressive task parallel algorithm; optimal algorithm; parallel algorithms; performance; projection-based transforms; shape detection; task parallelism; Concurrent computing; Contracts; Digital images; Distributed computing; Image edge detection; Parallel algorithms; Parallel processing; Pixel; Scalability; Shape;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Parallel Processing, 1997., Proceedings of the 1997 International Conference on
Conference_Location :
Bloomington, IL
ISSN :
0190-3918
Print_ISBN :
0-8186-8108-X
Type :
conf
DOI :
10.1109/ICPP.1997.622678
Filename :
622678
Link To Document :
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