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