A new edge detection algorithm for image corrupted by White-Gaussian noise

2007 ◽  
Vol 61 (8) ◽  
pp. 546-550 ◽  
Author(s):  
Qinghang He ◽  
Zhenxi Zhang
Keyword(s):  
Edge Detection ◽  
Gaussian Noise ◽  
Detection Algorithm ◽  
White Gaussian Noise ◽  
Edge Detection Algorithm

An Edge Detection Algorithm Based on Edge-Preserving

2016 ◽  
Vol 693 ◽  
pp. 1321-1325
Author(s):  
C.R. Tang ◽  
A. Li
Keyword(s):  
Edge Detection ◽  
Gaussian Noise ◽  
Detection Algorithm ◽  
Order Differential Operator ◽  
Boundary Extraction ◽  
Edge Preserving ◽  
Edge Information ◽  
Edge Detection Algorithm ◽  
First Order ◽  
Simulation Results

The traditional first-order differential operator is under the influence of the Gaussian noise, therefore, it often implement boundary extraction after average filtering. But the filtering process would often smooth the details of some directions of image too much, so that the edge cannot be extracted correctly. To solve this problem, this paper puts forward the edge detection algorithm based on edges keep, to determine the keeping direction of the edge through matching different directions’ edge template. Instead of average filtering process, it can improve the performance of traditional operator, and provide the simulation results. Experimental results show that the algorithm can eliminate noise, and at the same time, keep more edge information of the image.

Application of Improved Canny Edge Detection Algorithm in Coal-Rock Interface Recognition

2012 ◽  
Vol 220-223 ◽  
pp. 1279-1283 ◽  
Author(s):  
Li Hong Dong ◽  
Peng Bing Zhao
Keyword(s):  
Edge Detection ◽  
Detection Algorithm ◽  
Canny Edge Detection ◽  
Edge Detection Algorithm ◽  
Canny Edge ◽  
Rock Interface ◽  
Coal Rock ◽  
Image Edge ◽  
Canny Algorithm ◽  
Canny Edge Detection Algorithm

The coal-rock interface recognition is one of the critical automated technologies in the fully mechanized mining face. The poor working conditions underground result in the seriously polluted edge information of the coal-rock interface, which affects the positioning precision of the shearer drum. The Gaussian filter parameters and the high-low thresholds are difficult to select in the traditional Canny algorithm, which causes the information loss of gradual edge and the phenomenon of false edge. Consequently, this paper presents an improved Canny edge detection algorithm, which adopts the adaptive median filtering algorithm to calculate the thresholds of Canny algorithm according to the grayscale mean and variance mean. This algorithm can protect the image edge details better and can restrain the blurred image edge. Experimental results show that this algorithm has improved the edge extraction effect under the case of noise interference and improved the detection precision and accuracy of the coal-rock image effectively.

An Improved Edge Detection Algorithm Based on Canny Operator

2013 ◽  
Vol 347-350 ◽  
pp. 3541-3545 ◽  
Author(s):  
Dan Dan Zhang ◽  
Shuang Zhao
Keyword(s):  
Edge Detection ◽  
Detection Algorithm ◽  
Image Simulation ◽  
Edge Image ◽  
Canny Operator ◽  
Edge Detection Algorithm ◽  
Image Edge Detection ◽  
Canny Edge ◽  
Image Edge ◽  
Canny Edge Detection Algorithm

The traditional Canny edge detection algorithm is analyzed in this paper. To overcome the difficulty of threshold selecting in Canny algorithm, an improved method based on Otsu algorithm and mathematical morphology is proposed to choose the threshold adaptively and simultaneously. This method applies the improved Canny operator and the image morphology separately to image edge detection, and then performs image fusion of the two results using the wavelet fusion technology to obtain the final edge-image. Simulation results show that the proposed algorithm has better anti-noise ability and effectively enhances the accuracy of image edge detection.

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