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.