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Multiresolution Hough Transform-An Efficient Method of Detecting Patterns in Images
November 1992 (vol. 14 no. 11)
pp. 1090-1095

A new multiresolution coarse-to-fine search algorithm for efficient computation of the Hough transform is proposed. The algorithm uses multiresolution images and parameter arrays. Logarithmic range reduction is proposed to achieve faster convergence. Discretization errors are taken into consideration when accumulating the parameter array. This permits the use of a very simple peak detection algorithm. Comparative results using three peak detection methods are presented. Tests on synthetic and real-world images show that the parameters converge rapidly toward the true value. The errors in rho and theta , as well as the computation time, are much lower than those obtained by other methods. Since the multiresolution Hough transform (MHT) uses a simple peak detection algorithm, the computation time will be significantly lower than other algorithms if the time for peak detection is also taken into account. The algorithm can be generalized for patterns with any number of parameters.

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Index Terms:
discretisation errors; image recognition; multiresolution coarse-to-fine search algorithm; convergence; peak detection; multiresolution Hough transform; Hough transforms; image recognition; search problems
Citation:
M. Atiquzzaman, "Multiresolution Hough Transform-An Efficient Method of Detecting Patterns in Images," IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 14, no. 11, pp. 1090-1095, Nov. 1992, doi:10.1109/34.166623
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