Intermediate-level feature extraction in novel parallel environments

Authors:
Ville Kyrki;Jani Peusaari;Heikki Kälviäinen
Affiliations:
Lappeenranta University of Technology, Department of Information Technology, Laboratory of Information Processing, P.O. Box 20, 53851 Lappeenranta, Finland;Lappeenranta University of Technology, Department of Information Technology, Laboratory of Information Processing, P.O. Box 20, 53851 Lappeenranta, Finland;Lappeenranta University of Technology, Department of Information Technology, Laboratory of Information Processing, P.O. Box 20, 53851 Lappeenranta, Finland
Venue:
Machine Vision and Applications
Year:
2003

Citing 15
Cited 0

Fast Hough transform: A hierarchical approach

Computer Vision, Graphics, and Image Processing
Hough transform algorithms for mesh-connected SIMD parallel processors

Computer Vision, Graphics, and Image Processing
A new curve detection method: randomized Hough transform (RHT)

Pattern Recognition Letters
A probabilistic Hough transform

Pattern Recognition
Parallel Hough transform algorithm performance

Image and Vision Computing
Implementation and evaluation of Hough transform algorithms on a shared-memory multiprocessor

Journal of Parallel and Distributed Computing - Special issue on shared-memory multiprocessors
A probabilistic algorithm for computing Hough transforms

Journal of Algorithms
Which Hough transform?

CVGIP: Image Understanding
Pipelined implementation of the multiresolution Hough transform in a pyramid multiprocessor

Pattern Recognition Letters
An extension to the randomized Hough transform exploiting connectivity

Pattern Recognition Letters
Programming with POSIX threads

Programming with POSIX threads
Fast Hough transform on multiprocessors: a branch and bound approach

Journal of Parallel and Distributed Computing
Use of the Hough transformation to detect lines and curves in pictures

Communications of the ACM
High Performance Cluster Computing: Programming and Applications

High Performance Cluster Computing: Programming and Applications
Exploiting task and data parallelism in parallel Hough and Radon transforms

ICPP '97 Proceedings of the international Conference on Parallel Processing

Quantified Score

Hi-index	0.00

Visualization

Abstract

Parallel systems provide an approach to robust computing. The motivation for this work arises from using modern parallel environments in intermediate-level feature extraction. This study presents parallel algorithms for the Hough transform (HT) and the randomized Hough transform (RHT). The algorithms are analyzed in two parallel environments: multiprocessor computers and workstation networks. The results suggest that both environments are suitable for the parallelization of HT. Because scalability of the parallel RHT is weaker than with HT, only the multiprocessor environment is suitable. The limited scalability forces us to use adaptive techniques to obtain good results regardless of the number of processors. Despite the fact that the speedups with HT are greater than with RHT, in terms of total computation time, the new parallel RHT algorithm outperforms the parallel HT.