DocumentCode :
2168840
Title :
Edge Detection by Adaptive Neuro-Fuzzy Inference System
Author :
Zhang, Lei ; Xiao, Mei ; Ma, Jian ; Song, HongXun
Author_Institution :
Sch. of Automobile, Chang´´an Univ., Sian, China
fYear :
2009
fDate :
17-19 Oct. 2009
Firstpage :
1
Lastpage :
4
Abstract :
Neuro-fuzzy (NF) systems are very suitable tools to deal with uncertainty encountered in the process of extracting useful information from images. We present a novel adaptive neuro-fuzzy inference system (ANFIS) for edge detection in digital images. The internal parameters of the proposed ANFIS edge detector are optimized by training using very simple artificial images. The edges are directly determined by ANFIS network. The proposed ANFIS edge detector is tested on popular images having different image properties and also compared with popular edge detectors from the literature. Experimental results show that the proposed ANFIS edge detector exhibits much better performance than the competing operators and may efficiently be used for the detection of edges in digital images.
Keywords :
computer vision; edge detection; feature extraction; fuzzy neural nets; fuzzy reasoning; ANFIS; adaptive neuro-fuzzy inference system; artificial image; edge detection; image information extraction; machine vision; Adaptive systems; Data mining; Detectors; Digital images; Fuzzy logic; Fuzzy systems; Image edge detection; Image processing; Noise measurement; Uncertainty;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Image and Signal Processing, 2009. CISP '09. 2nd International Congress on
Conference_Location :
Tianjin
Print_ISBN :
978-1-4244-4129-7
Electronic_ISBN :
978-1-4244-4131-0
Type :
conf
DOI :
10.1109/CISP.2009.5304595
Filename :
5304595
Link To Document :
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