The University of Southampton
University of Southampton Institutional Repository

Improving Parameter Space Decomposition for the Generalised Hough Transform

Improving Parameter Space Decomposition for the Generalised Hough Transform
Improving Parameter Space Decomposition for the Generalised Hough Transform
The Generalised Hough Transform extracts arbitrary objects by using a non-analytic model shape representation obtained from gradient direction and scale are unknown. In this paper we present a novel representation of a model shape defined by the geometric relationship given by the position of a collection of edge points. This representation avoids errors due to unreliable gradient direction information and is used to reduce the computational requirements by decomposing the four-dimensional parameter space into two two-dimensional sub-spaces. Experimental results show the efficacy of the new technique for extracting shapes from synthetic and real images.
627--630
Aguado, A.S.
ad7e99c5-47ab-4f88-849a-c6e6d77e4200
Montiel, M.E.
4aefa43d-aeb9-4151-83f5-31fbab5664ba
Nixon, M.S.
2b5b9804-5a81-462a-82e6-92ee5fa74e12
Aguado, A.S.
ad7e99c5-47ab-4f88-849a-c6e6d77e4200
Montiel, M.E.
4aefa43d-aeb9-4151-83f5-31fbab5664ba
Nixon, M.S.
2b5b9804-5a81-462a-82e6-92ee5fa74e12

Aguado, A.S., Montiel, M.E. and Nixon, M.S. (1996) Improving Parameter Space Decomposition for the Generalised Hough Transform At Proc. IEEE International Conference on Image Processing ICIP '96. , 627--630.

Record type: Conference or Workshop Item (Other)

Abstract

The Generalised Hough Transform extracts arbitrary objects by using a non-analytic model shape representation obtained from gradient direction and scale are unknown. In this paper we present a novel representation of a model shape defined by the geometric relationship given by the position of a collection of edge points. This representation avoids errors due to unreliable gradient direction information and is used to reduce the computational requirements by decomposing the four-dimensional parameter space into two two-dimensional sub-spaces. Experimental results show the efficacy of the new technique for extracting shapes from synthetic and real images.

Full text not available from this repository.

More information

Published date: 1996
Venue - Dates: Proc. IEEE International Conference on Image Processing ICIP '96, 1996-01-01
Organisations: Southampton Wireless Group

Identifiers

Local EPrints ID: 250056
URI: http://eprints.soton.ac.uk/id/eprint/250056
PURE UUID: 4722f8d3-3903-4686-a10f-3dcaf4edea37

Catalogue record

Date deposited: 04 May 1999
Last modified: 18 Jul 2017 10:44

Export record

Contributors

Author: A.S. Aguado
Author: M.E. Montiel
Author: M.S. Nixon

University divisions

Download statistics

Downloads from ePrints over the past year. Other digital versions may also be available to download e.g. from the publisher's website.

View more statistics

Atom RSS 1.0 RSS 2.0

Contact ePrints Soton: eprints@soton.ac.uk

ePrints Soton supports OAI 2.0 with a base URL of http://eprints.soton.ac.uk/cgi/oai2

This repository has been built using EPrints software, developed at the University of Southampton, but available to everyone to use.

We use cookies to ensure that we give you the best experience on our website. If you continue without changing your settings, we will assume that you are happy to receive cookies on the University of Southampton website.

×