Corner Detection Based on Normal Vector of Boundary Fitting Line

This paper shows a novel and low complexity approach for corner detection which is based on a normal vector of boundary fitting line. It avoids wrong detection of superfluous corners on no-corner arcs. Our proposed method is superior to Sun´s k-cosine corner detection in detection time and has a better performance in localization. Our experiment results confirmed that the proposed approach of corner detection has reached our goal. It is free from rotation and able to locate the corner correctly. In addition, it also performs well for scaling images with the adjustable thresholds.