The fast multi-level fuzzy edge detection of blurry images
Ke Mu, Jianhui Yang
COMPUTER MODELLING & NEW TECHNOLOGIES 2013 17(5B) 28-31
School of Mathematics and Statistics, Zhoukou Normal University, Zhoukou 466000, China
To realize the fast and accurate detection of the edges from the blurry images, the fast multi-level fuzzy edge detection (FMFED) algorithm is proposed. The FMFED algorithm first enhances the image contrast by means of the fast multi-level fuzzy enhancement (FMFE) algorithm using the simple transformation function based on two image thresholds. Second, the edges are extracted from the enhanced image by the two-stage edge detection operator which identifies the edge candidates based on the local characteristics of the image and then determines the true edge pixels using the edge detection operator based on the extreme of the gradient values. Experimental results demonstrate that the FMFED algorithm can extract the thin edges and remove the false edges from the image, which leads to its better performance than the Sobel operator, Canny operator, traditional fuzzy edge detection algorithm and other multi-level fuzzy edge detection algorithms.