Radon and projection transform-based computer vision: algorithms, a pipeline architecture, and industrial applications
Hough transform algorithms for mesh-connected SIMD parallel processors
Computer Vision, Graphics, and Image Processing
Parallel algorithms for line detection on a mesh
Journal of Parallel and Distributed Computing
Hypercube algorithms: with applications to image processing and pattern recognition
Hypercube algorithms: with applications to image processing and pattern recognition
The Hough transform has O(N) complexity on N×-N mesh connected computers
SIAM Journal on Computing
A skimming technique for fast accurate edge detection
Signal Processing
Exploiting task and data parallelism on a multicomputer
PPOPP '93 Proceedings of the fourth ACM SIGPLAN symposium on Principles and practice of parallel programming
Using MPI: portable parallel programming with the message-passing interface
Using MPI: portable parallel programming with the message-passing interface
Parallel algorithms for VLSI layout verification
Journal of Parallel and Distributed Computing
Digital Image Processing
Automatic Extraction of Functional Parallelism from Ordinary Programs
IEEE Transactions on Parallel and Distributed Systems
Compiling MATLAB Programs to ScaLAPACK: Exploiting Task and Data Parallelism
IPPS '96 Proceedings of the 10th International Parallel Processing Symposium
Integrating Task and Data Parallelism in an Irregular Application: A Case Study
SPDP '96 Proceedings of the 8th IEEE Symposium on Parallel and Distributed Processing (SPDP '96)
ICPP '94 Proceedings of the 1994 International Conference on Parallel Processing - Volume 02
Intermediate-level feature extraction in novel parallel environments
Machine Vision and Applications
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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.