OPTIMAL RAMP EDGE-DETECTION USING EXPANSION MATCHING

In practical images, ideal step edges are actually transformed into ra mp edges, due to the general low pass filtering nature of imaging syst ems. This pager discusses the application of the recently developed Ex pansion Matching (EXM) method for optimal ramp edge detection, EXM opt imizes a novel matching criterion called Discriminative Signal-to-Nois e Ratio (DSNR) and has been shown to robustly recognize templates unde r conditions of noise, severe occlusion, and superposition. We show th at our ramp edge detector performs better than the ramp detector obtai ned from Canny's criteria in terms oi DSNR and is relatively easier to derive for various noise levels and slopes.