Fast and Robust Fuzzy Edge Detection

In recent years, fuzzy techniques have been applied to develop new edge detection techniques because they offer a flexible framework for edge extraction with respect to specific requirements. These techniques, however, are usually expensive in computing compared to classical approaches like the Sobel operator. In many practical applications we need fast edge detection. In this chapter, several fast methods are proposed which are suitable for cases where a rough edge estimation is required. On the other side, the result of edge detection techniques in noisy environments is often not satisfactory. In this chapter, also a robust algorithm based on fuzzy if-then rules is proposed that can detect edges and lines in noisy images.

[1]  Fabrizio Russo,et al.  FIRE operators for image processing , 1999, Fuzzy Sets Syst..

[2]  James C. Bezdek,et al.  Enhancement and analysis of digital mammograms using fuzzy models , 1998, Other Conferences.

[3]  Sankar K. Pal A measure of edge ambiguity using fuzzy sets , 1986, Pattern Recognit. Lett..

[4]  Hamid R. Tizhoosh,et al.  Fuzzy Image Processing , 2000, Computer Vision and Applications.

[5]  F. Russo,et al.  Edge extraction by FIRE operators , 1994, Proceedings of 1994 IEEE 3rd International Fuzzy Systems Conference.

[6]  Kenneth H. L. Ho,et al.  FEDGE - Fuzzy Edge Detection by Fuzzy Categorization and Classification of Edges , 1995, Fuzzy Logic in Artificial Intelligence.

[7]  James C. Bezdek,et al.  A geometric approach to edge detection , 1998, IEEE Trans. Fuzzy Syst..

[8]  Sankar K. Pal,et al.  Fuzzy Mathematical Approach to Pattern Recognition , 1986 .