• 中国计算机学会会刊
  • 中国科技核心期刊
  • 中文核心期刊

J4 ›› 2014, Vol. 36 ›› Issue (03): 491-496.

• 论文 • Previous Articles     Next Articles

Image edge detection method of underground
objects based on improved Canny operator             

SHANG Changchun,MA Hongwei,AN Jingyu   

  1. (Engineering Training Center,Xi’an University of Science and Technology,Xi’an 710054,China)
  • Received:2013-01-07 Revised:2013-05-21 Online:2014-03-25 Published:2014-03-25

Abstract:

In view of the shortage of the traditional Canny algorithm in detecting the low intensity edge capacity, the  improved edge detection method is carried out from the following three aspects: (1) Using a new fourorder partial differential equations of the noise reduction algorithm for image denoising, it can further improve the noise reduction effect and better preserve image details in the noise reduction process, so that the underground objects are more easily detected. (2) Using an adaptive threshold method for the image edge detection, the method realizes the adaptive dual threshold extraction, which can effectively extract the real edge. Especially in the edge extraction of low contrast image, this method has more advantages.  (3) Using the theory of fuzzy decision, an effective edge connection method is proposed based on the traditional Canny algorithm. Finally, in order to verify the effect of Canny edge detection operator, Prewitt, Robert, Sobel, and traditional Canny algorithms are used to perform the underground image edge detection test. The results show that the new method can detect more lowintensity edge and inhibit the noise at the greatest degree. It gives the foundation for the robot image recognition in coal mine.

Key words: canny operator;Otsu algorithm;Gauss Laplasse transform