A Dynamic Combinatorial Hough Transform for Straight Lines and Circles

A new algorithm for the Hough transform is presented. It uses information available in the distribution of image points to calculate the parameters associated with combinations of the minimum number of points necessary to define an instance of the shape under detection. The method requires only one dimensional accumulation of evidence to determine the parameters associated with a given shape. Using the algorithm, the Hough transform of sparse images is more efficiently calculated. Dense images may be segmented and similarly processed. The method also provides a feedback mechanism between image and transform space whereby contiguity of feature points and endpoints of curves may be determined.

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