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Edge Extraction Using Fuzzy Reasoning

  • Todd Law
  • Koji Yamada
  • Daisuke Shibata
  • Tsuyoshi Nakamura
  • Lifeng He
  • Hidenori Itoh
Part of the Studies in Fuzziness and Soft Computing book series (STUDFUZZ, volume 42)

Abstract

We characterize the problem of detecting edges in images as a fuzzy reasoning problem. The edge detection problem is divided into three stages: filtering, detection, and tracing. Images are filtered by applying fuzzy reasoning based on local pixel characteristics to control the degree of Gaussian smoothing. Filtered images are then subjected to a simple edge detection algorithm which evaluates the edge fuzzy membership value for each pixel, based on local image characteristics. Finally, pixels having high edge membership are traced and assembled into structures, again using fuzzy reasoning to guide the tracing process. The filtering, detection, and tracing algorithms are tested on several test images. Comparison is made with a standard edge detection technique.

Keywords

Fuzzy Rule Edge Detection Triple Point Edge Point Normalize Mean Square Error 
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

  • Todd Law
    • 1
  • Koji Yamada
    • 2
  • Daisuke Shibata
    • 2
  • Tsuyoshi Nakamura
    • 2
  • Lifeng He
    • 3
  • Hidenori Itoh
    • 2
  1. 1.Hewlett-Packard Japan, Ltd.HyogoJapan
  2. 2.Department of Intelligence and Computer ScienceNagoya Institute of TechnologyNagoyaJapan
  3. 3.Faculty of Information Science and TechnologyAichi Prefectural UniversityAichiJapan

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