Fuzzy Interpretation of Image Data

  • Joon H. Han
  • Tae Y. Kim
  • László T. Kóczy
Part of the Studies in Fuzziness and Soft Computing book series (STUDFUZZ, volume 42)


In image formation, we usually consider two things: the intensity and the location of a pixel. Because of several reasons, there could be uncertainty in the image brightness and also in the location of a pixel. We consider the cases where the observed image data or entities computed from it are inherently fuzzy. Based on this idea, we have considered shape detection methods and representation of edges using fuzzy set theory. In shape detection method, an image point is considered as a fuzzy data. By combining this concept and the Hough transform algorithm, a fuzzy Hough transform algorithm is introduced. More general shape detection paradigm is given by defining the cardinality of a shape. Edges, which is one of the basic entities of an image, is generalized using the fuzzy set theory. An edge evaluation criteria for the edges are also presented.


Membership Function Fuzzy Membership Edge Image Hough Transform Fuzzy Data 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2000

Authors and Affiliations

  • Joon H. Han
    • 1
  • Tae Y. Kim
    • 1
  • László T. Kóczy
    • 2
  1. 1.Dept. of Computer Science and EngineeringPohang University of Science and TechnologyPohangRepublic of Korea
  2. 2.Dept. of Telecommunication and TelematicsTechnical University of BudapestBudapestHungary

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