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Method of edge detection based on fuzzy entropy and FKCN

  • Bao Ping Wang
  • , Sheng Hu Liu
  • , Jia Tian Zhang
  • , Yan Ning Zhang
  • , Jiu Lun Fan
  • Xi'an Shiyou University
  • Northwestern Polytechnical University Xian
  • Xi'an Institute of Posts and Telecommunications

Research output: Contribution to journalArticlepeer-review

13 Scopus citations

Abstract

The three natural characters of image edge are that the gray intensity distribution in neighborhood of image is ordered, directive, and structurized. Through quoting fuzzy entropy, the authors construct three information measures fuzzy entropy-based to describe the natural characters of image edge. Three component vectors for describing three natural characters of image edge are gotten via trained image samples. Firstly, a fuzzy Kohonen clustering network (FKCN) is trained with some feature vector consist of the three component vectors, and then the edge points in a new image are directly extracted by using the trained FKCN. The method does not need any threshold; more sensitive for weak edge detection; has better anti-noise performance since the influence of noise is adequately considered when the feature vector is selected.

Original languageEnglish
Pages (from-to)664-669
Number of pages6
JournalJisuanji Xuebao/Chinese Journal of Computers
Volume29
Issue number4
StatePublished - Apr 2006

Keywords

  • Edge detection
  • Fuzzy entropy
  • Fuzzy Kohonen clustering network

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