A new image edge detection algorithm based on improved Canny

摘要

Due to the filter and threshold setting method, the traditional Canny algorithm has the disadvantages of limited denoising ability and poor adaptive ability. Focusing on the filtering part and the threshold setting part, a new image edge detection algorithm based on improved Canny was proposed. In the new algorithm, the Gaussian filtering algorithm is replaced by an improved filtering algorithm, in which the filtering method, weighting method and the size of the filtering window are adaptively selected according to the noise density. In addition, the OTSU algorithm is used to figure out the upper threshold. And an evalution function based on the gradient magnitude histogram and intra-class variance minimization is introduced to help determine the lower threshold The Lena images with differernt pepper and salt noise density were taken as the experiment object. Both the subjective and objective evalution were carried out to verify that the algorithm proposed in this paper has good denoising ability and detail retention ability and that when pepper and salt noise density grows, the new algorithm has more advantages over the adaptive median filtering Canny algorithm and the adaptive weighting median filtering Canny algorithm.