Abstract A new algorithm for computing the Hough transform is presented. It calculates the parameters associated with all possible combinations of two-point line segments among the feature points in the image, rather than calculating all possible values of one of the parameters searched. It uses information available in the distribution of image points, rather than depending solely on information extracted from the transform space. Using the algorithm, the Hough transform of sparse images is more efficiently calculated. Dense images may be segmented and similarly processed. The transform space obtained by this algorithm contains less extraneous data and more significant maxima, thus making it easier to extract the desired parameters from it.
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