DocumentCode :
3469301
Title :
A fast edge detection using fuzzy rules
Author :
Talai, Z. ; Talai, Armin
Author_Institution :
Comput. Sci. Dept., Badji Mokhtar Univ. Annaba, Annaba, Algeria
fYear :
2011
fDate :
3-5 March 2011
Firstpage :
1
Lastpage :
5
Abstract :
In computer vision and image processing edge detection is an important topic. In what follows, a simple edge detection and fast calculation method using fuzzy rules is presented. The fuzzy rule system is designed to model edge continuity criteria. To adjust parameters the maximum entropy principle is used for. We also discuss the related issues in designing fuzzy edge detectors. Every step of evolution of the detector we compare it with popular edge detectors: Canny edge detector. The proposed fuzzy edge detector does not need parameter setting as Canny´s; also it can preserve an appropriate detection in details. High level noise does not affect the detection, in addition it can work well under situations that other edge detectors cannot. The filtering process is unnecessary because the detector efficiently extracts edges in images corrupted by noise without requiring it. The experimental results demonstrate the superiority of the proposed method.
Keywords :
computer vision; edge detection; fuzzy logic; maximum entropy methods; Canny edge detector; computer vision; edge continuity criteria; edge detection; fuzzy edge detectors; fuzzy rule system; image processing; maximum entropy principle; Detectors; Entropy; Filtering; Image edge detection; Image segmentation; Noise; Roads; Edge Detection; Fuzzy Inference Rules; Fuzzy Logic; Image Processing; Maximum Entropy Principle; Segmentation;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Communications, Computing and Control Applications (CCCA), 2011 International Conference on
Conference_Location :
Hammamet
Print_ISBN :
978-1-4244-9795-9
Type :
conf
DOI :
10.1109/CCCA.2011.6031499
Filename :
6031499
Link To Document :
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