Adaptive fuzzy edge detector for image enhancement

Author

Lee, Chang-Shing ; Kuo, Yau-Hwang

Author_Institution

Inst. of Inf. Eng., Nat. Cheng Kung Univ., Tainan, Taiwan

Volume

2

fYear

1998

fDate

4-9 May 1998

Firstpage

1542

Abstract

A novel adaptive fuzzy edge detector for image enhancement, which can work well in full range of random impulse noise probability and perform efficiently in the environment of mixed Gaussian impulse noise, is proposed. It is an extended adaptive weighted fuzzy mean (EAWFM) filter, which combines adaptive weighted fuzzy mean filter and fuzzy normed inference system to efficiently perform edge detection in smeared images. The membership functions of all fuzzy sets used in EAWFM can be adaptively determined for different images, and EAWFM filter is capable of converting blurred edges to clear ones and suppressing noise at the same time. The important properties of EAWFM filter are analyzed and some experimental results are presented to show its excellent performance

Keywords

Gaussian noise; adaptive filters; edge detection; fuzzy logic; fuzzy set theory; image enhancement; inference mechanisms; knowledge based systems; Gaussian impulse noise; adaptive fuzzy edge detector; adaptive weighted fuzzy mean filter; blurred edges; edge detection; fuzzy inference; fuzzy logic; fuzzy set theory; image enhancement; knowledge based systems; membership functions; probability; random impulse noise; Adaptive filters; Detectors; Fuzzy sets; Fuzzy systems; Gaussian noise; Image converters; Image edge detection; Image enhancement; Performance analysis; Working environment noise;

fLanguage

English

Publisher

ieee

Conference_Titel

Fuzzy Systems Proceedings, 1998. IEEE World Congress on Computational Intelligence., The 1998 IEEE International Conference on

Conference_Location

Anchorage, AK

ISSN

1098-7584

Print_ISBN

0-7803-4863-X

Type

conf

DOI

10.1109/FUZZY.1998.686348

Filename

686348