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An inherent probabilistic aspect of the Hough transform

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Abstract

In this paper, a new property of the Hough transform is discovered, namely an inherent probabilistic aspect which is independent of the input image and embedded in the transformation process from the image space to the parameter space. It is shown that such a probabilistic aspect has a wide range of implications concerning the specification of implementation schemes and the performance of Hough transform. In particular, it is shown that in order to make the Hough transform really meaningful, an appropriate curve (surface) density function must be, either explicitly or implicitly, supplied during its implementation process, and that the widely used approach to uniformly discretizing parameter space in the literature is generally inadequate.

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Authors and Affiliations

  1. National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, 100080, Beijing, P.R. China

    Hu Zhanyi, Yang Changjiang, Yang Yi & Ma Songde

Authors
  1. Hu Zhanyi
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  2. Yang Changjiang
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  3. Yang Yi
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  4. Ma Songde
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Corresponding author

Correspondence to Hu Zhanyi.

Additional information

This work was supported by the National Natural Science Foundation of China and the ‘863’ National Hi-Tech Development Program.

HU Zhanyi was born in 1961. He received his B.S. degree in automation from the North China University of Technology in 1985, M.S. and Ph.D. degrees in electronic engineering from the University of Liege, Belgium, in 1988 and 1993, respectively. Now he is a Professor at the National Laboratory of Pattern Recognition, Chinese Academy of Sciences. His research interests include robot self-location, object reconstruction, Hough transform, active vision and camera calibration.

YANG Changjiang received the B.S. degree in automation from the University of Science and Technology of China in 1996. He is now pursuing his M.S. degree in the National Laboratory of Pattern Recognition, Chinese Academy of Sciences. His research interests include image processing, computer vision, and pattern recognition.

YANG Yi received the B.S. degree in automation from the Hua Zhong Politechnical University in 1995. Now he is pursuing his M.S. degree in the National Laboratory of Pattern Recognition, Chinese Academy of Sciences. His research interests include robot navigation, geometric feature extraction, object reconstruction.

For the biography ofMA Songde, please refer to p.92 of this issue.

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Hu, Z., Yang, C., Yang, Y. et al. An inherent probabilistic aspect of the Hough transform. J. Comput. Sci. & Technol. 14, 44–48 (1999). https://doi.org/10.1007/BF02952486

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  • DOI: https://doi.org/10.1007/BF02952486

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