Directional second order derivatives: Application to edge and corner detection

In this paper, we propose an adaptive scheme to design directional second order derivatives orthogonally and tangentially to the local edge. The principle lies on the definition of two adaptive filter masks which estimate the two derivatives along the normal (n) and tangential (t) directions. Both filter masks are controlled by an adaptive mask whose coefficients are tuned in accordance with the local grey level distribution. The two new filters are then applied respectively to edge and corner detection : edge detection is achieved by detecting the zero-crossing of the derivative along n. and corner detection is obtained by thresholding the amplitude of the derivative along t. Results of these detections are provided on synthetise and real-world images, and swow the robustness of the new proposed approach.