Sub-Pixel Edge Detection for Precision Measurement Based on Canny Criteria

2005 ◽  
Vol 295-296 ◽  
pp. 711-716 ◽  
Author(s):  
S.H. Xie ◽  
Qiu Liao ◽  
S.R. Qin
Keyword(s):  
Edge Detection ◽  
Precision Measurement ◽  
High Frequency ◽  
Frequency Component ◽  
High Frequency Component ◽  
Interpolation Algorithm ◽  
Interpolation Scheme ◽  
Initial Image ◽  
Canny Edge Detection ◽  
Canny Edge

A new nonlinear intensity interpolation algorithm is presented to realize sub-pixel edge detection. The interpolation algorithm based on the Canny criteria makes full use of grads information attained by Canny edge detection to perform special interpolation in the grads direction. When the resolution is enhanced, the interpolated image by the new interpolation scheme can efficiently preserve high frequency component in the original image. The edge detection of interpolated image permits high precision localization. The new interpolation algorithm is more effective in reserving the grads information of the step edge of the initial image than the usual linear interpolations. It requires simpler computation than the present non-linear interpolations.

Wavelet De-Noising Algorithm Based on OpenCV for Images Edge Detection

2014 ◽  
Vol 989-994 ◽  
pp. 3973-3976
Author(s):  
Yi Fan Ma ◽  
Shu Gui Liu
Keyword(s):  
Edge Detection ◽  
High Frequency ◽  
Low Frequency ◽  
Frequency Signal ◽  
High Frequency Signal ◽  
Canny Edge Detection ◽  
Image Edge Detection ◽  
Canny Edge ◽  
Image Edge ◽  
Wavelet Algorithm

Image edge detection is easily affected by noise. Wavelet algorithm can divide the image into low frequency and high frequency. By the processing of high frequency signal and the reconstruction of wavelet coefficients, the purpose of removing noise can be achieved. In the environment of VC++6.0, an image de-noising algorithm based on the wavelet combined with the Canny edge detection is proposed, which obtains a good result. The above algorithms are implemented based on OpenCV, which is more efficient, providing the conditions for subsequent image analysis and recognition. Experiments are carried out and the results show that the proposed algorithm is available and has a good performance.

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.

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