Abstract
Based on three different implementation schemes, this paper strongly demonstrates that the performance of the Hough transform depends crucially on its implementation scheme when it is used for line detection. Moreover, the obtained results can be used as a theoretical basis to predict the performance of the Hough transform as well as to eliminate the noise in Hough space coming from image noise.
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This work was partly supported by the 863 Hi-Tech Programme and the National Natural Science Foundation of China.
Hu Zhanyi was born in Shanxi province, P.R. China in 1961. He received his B.S. degree in automation from North China University of Technology in 1985, and his M.S. and Ph.D. degrees in computer science from the University of Liege, Belgium, in 1988 and 1993, respectively. Now he is an Associate Professor in the National Laboratory of Pattern Recognition, Chinese Academy of Sciences. His research interests include image processing, computer vision, and pattern recognition. E-mail address: huzy@prlsun5.ia.ac.cn
Ma Songde was born in Shanghai, P.R. China in 1946. He received his B.S. degree in automation from Tsinghua University in 1969, and the degrees of Docteur de 3 ieme cycle and of Docteur d’Etat from University of Paris VI in 1983 and 1986, respectively. From 1983 to 1984 he was an invited researcher in the Computer Vision Laboratory, University of Maryland. From 1984 to 1986 he was an invited researcher in the Robotic Vision Group of INRIA in France. Since 1986 he has been a Professor at the National Laboratory of Pattern Recognition, Institute of Automation, Chinses Academy of Sciences. His current research interests include 3D computer vision, neural computing, realistic image synthesis and sensor based robot control.
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Hu, Z., Ma, S. Performance prediction of the hough transform. J. of Comput. Sci. & Technol. 12, 49–57 (1997). https://doi.org/10.1007/BF02943144
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DOI: https://doi.org/10.1007/BF02943144