A NOVEL HOUGH TRANSFORM BASED ON ELIMINATING PARTICLE SWARM OPTIMIZATION AND ITS APPLICATIONS

DOI

10.2991/jcis.2008.40How to use a DOI?

Keywords

Hough transform, Particle swarm optimization, Eliminating PSO, Curve detection.

Abstract

Hough transform (HT) is a well estab-lished method for curve detection and recognition due to its robustness and in-sensitiveness to noise, and its parallel processing capability. However, HT is quite time-consuming. In this paper, an eliminating particle swarm optimization (EPSO) algorithm is studied to improve the speed of a Hough transform. The so-lutions of Hough transformation are con-sidered as the particles positions, and the EPSO algorithm searches the optimum solution by eliminating the “weakest” particles to speed up the computation. An accumulation array in Hough transforma-tion is utilized as a fitness function of the EPSO algorithm. The experiments on numerous images show that the proposed approach can be used to detect curves or contours of both noise-free and noisy im-ages with much better performance. Es-pecially, for noisy images, it can archive much better results than that obtained by using the existing HT algorithms.

Copyright

© 2008, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Yanhui Guo
AU  - H.D. Cheng
AU  - Wei Zhao
AU  - Yingtao Zhang
PY  - 2008/12
DA  - 2008/12
TI  - A NOVEL HOUGH TRANSFORM BASED ON ELIMINATING PARTICLE SWARM OPTIMIZATION AND ITS APPLICATIONS
BT  - Proceedings of the 11th Joint Conference on Information Sciences (JCIS 2008)
PB  - Atlantis Press
SP  - 232
EP  - 237
SN  - 1951-6851
UR  - https://doi.org/10.2991/jcis.2008.40
DO  - 10.2991/jcis.2008.40
ID  - Guo2008/12
ER  -