An Improved Canny Edge Detection Algorithm

Traditional Canny edge detection algorithm uses a global threshold selection method, when large changes are in the background of the image and the target gray, global threshold method may lose some local edge information. For this problem, this paper therefore proposes an adaptive dynamic threshold improved Canny edge detection algorithm. The method uses image gradient variance as the criterion of the image block according to the four forks tree principle, then uses the Otsu method to get the corresponding sub-block threshold value for each sub-block, and obtains threshold value matrix by interpolation, finally, gets image edge with improved edge connected algorithm. Experimental results show that, the algorithm not only has good anti-noise performance, but also better detection accuracy.