Generalized Fuzzy Hough Transform for Detecting Arbitrary Shapes in a Vague and Noisy Image

  • Authors:

  • Noriaki Suetake;Eiji Uchino;Kanae Hirata

  • Affiliations:

  • Department of Physics, Biology and Informatics, Yamaguchi University, 1677-1 Yoshida, 753-8512, Yamaguchi, JAPAN;Department of Physics, Biology and Informatics, Yamaguchi University, 1677-1 Yoshida, 753-8512, Yamaguchi, JAPAN;Department of Physics, Biology and Informatics, Yamaguchi University, 1677-1 Yoshida, 753-8512, Yamaguchi, JAPAN

  • Venue:
  • Soft Computing - A Fusion of Foundations, Methodologies and Applications
  • Year:
  • 2006

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Abstract

A generalized Hough transform is an effective method for an arbitrary shape detection in a contour image. However, the conventional generalized Hough transform is not suitable for a noisy and blurred image. This paper describes a generalized fuzzy Hough transform which is derived by fuzzifying the vote process in the Hough transform. The present generalized fuzzy Hough transform enables a detection of an arbitrary shape in a very noisy, blurred, and even distorted image. The effectiveness of the present method has been confirmed by some preliminary experiments for artificially produced images and for actual digital images taken by an ordinary digital camera