An improved canny edge detection algorithm

The traditional Canny algorithm has been applied to image edge detection. However, this traditional algorithm can't adaptively determine the filtering threshold value and it can't separate targets from background, when filtering the lower contrast image. Therefore, in response to these problems, this paper proposed an improved method on Canny algorithm. Two adaptive thresholds were obtained by doing differential operation on amplitude gradient histogram. Then we connected edge points to get some generalized chains. After that, it needed to calculate their mean value to delete generalized chains, which are smaller than the mean value. Finally, the image edge detection results were got by linear fitting method. Experimental results show that the improved algorithm is more robust to noise and it can clearly separate targets from background.