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.
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Nixon, M.S.
2b5b9804-5a81-462a-82e6-92ee5fa74e12
1996
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.
Proc. IEEE International Conference on Image Processing ICIP '96.
.
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Conference or Workshop Item
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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.
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Published date: 1996
Venue - Dates:
Proc. IEEE International Conference on Image Processing ICIP '96, 1996-01-01
Organisations:
Southampton Wireless Group
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Local EPrints ID: 250056
URI: http://eprints.soton.ac.uk/id/eprint/250056
PURE UUID: 4722f8d3-3903-4686-a10f-3dcaf4edea37
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Date deposited: 04 May 1999
Last modified: 08 Jan 2022 02:32
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Author:
A.S. Aguado
Author:
M.E. Montiel
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