Three-dimensional contour edge detection algorithm

2000 ◽  
Author(s):  
Yizhou Wang ◽  
Sim Heng Ong ◽  
Ashraf A. Kassim ◽  
Kelvin W. C. Foong
Keyword(s):  
Edge Detection ◽  
Three Dimensional ◽  
Detection Algorithm ◽  
Edge Detection Algorithm

Agent Searching Edge Detection Algorithm for Bone Images

2012 ◽  
Vol 433-440 ◽  
pp. 6453-6456
Author(s):  
Hong Guang Zhang ◽  
Yuan’ An Liu ◽  
Bi Hua Tang ◽  
Zhi Peng Jia ◽  
Yan Qin
Keyword(s):  
Image Segmentation ◽  
Edge Detection ◽  
Feature Vector ◽  
Three Dimensional ◽  
Detection Algorithm ◽  
Experimental Results ◽  
Human Skeleton ◽  
Edge Detection Algorithm ◽  
Vector Correlation ◽  
Computer Aided

Bone image segmentation is the important technology for computer aided bone diagnosis system and the foundation for three-dimensional visualization of the human skeleton. Agent searching edge detection algorithm for bone images is proposed. Based on neighbor region correlation and regional harmonic mean feature vector correlation, different species of agent accomplish searching bone edge and experimental results are satisfactory. Experimental results comparison about the proposed algorithm, Prewitt, Sobel, Log and Canny is illustrated that demonstrates the proposed algorithm has advantages in some respects.

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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