Edge detection algorithm using shape-adaptive anisotropic differential filter

The traditional differential filter with fixed parameter has defects that it is difficult to precisely detect the edges of different type and is noise-sensitive. Therefore, an edge detection algorithm based on the shape-adaptive anisotropic differential filter is proposed. Using the differential autocorrelation matrix constructs a measure which can reflect the type of edge in image. Then, a map function from the measure to the anisotropic factor of anisotropic Gaussian directional derivative (ANDD) filter is designed to achieve the goal of adaptively controlling the shape of ANDD filter and progress to extract the precise edge strength map of different type. The ANDD filter with large scale improves the robustness of the edge strength map to noise. The experimental results show that the pratt figure of merit (FOM) of the proposed algorithm is respectively improved by 23.3%, 14. 5% and 9.5% compared with the Canny edge detection algorithm, the Gabor-based edge detection and the measure fusion-based edge detection algorithm under noise-free situation, and is respectively improved by 41.7%, 29.7% and 12.0% under noisy situation. © 2016, Editorial Office of Systems Engineering and Electronics. All right reserved.