Improving Parameter Space Decomposition for the Generalised Hough Transform
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 IEEE, 627--630.
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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.
|Item Type:||Conference or Workshop Item (UNSPECIFIED)|
|Divisions:||Faculty of Physical Sciences and Engineering > Electronics and Computer Science > Comms, Signal Processing & Control
|Date Deposited:||04 May 1999|
|Last Modified:||02 Mar 2012 13:39|
|Contributors:||Aguado, A.S. (Author)
Montiel, M.E. (Author)
Nixon, M.S. (Author)
|Further Information:||Google Scholar|
|ISI Citation Count:||0|
|RDF:||RDF+N-Triples, RDF+N3, RDF+XML, Browse.|
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