Real-Time Corner Detection in Binary Image
二值图像中拐点的实时检测算法

Presents a new real time corner detection algorithm. Corners are important information carriers in object recognition. Accurate, stable and fast detecting corners in digital image are common problems facing to corner detectors. Aiming at these problems and different from traditional corner detection algorithms, based on chain code, the algorithm constructs k(k>8) neighborhood chain codes of pixels and uses these chain codes to describe contours. Based on the differential definition of curvature, a curvature function is derived from k neighborhood chain codes. Corners are detected as those contour pixels, whose curvature the is largest in a lobe of contour curvature histogram. Convex and concave corners can be differentiated quickly by checking color attributes of pixels between corner edges. To validate the algorithm, tests comparing the new algorithm to 4 corner detection algorithms are given. The results show the new algorithm is not only accurate and stable, but also simple and fast, which make the algorithm suitable for the embedded computation environment.