Applications of Algebraic Moments for Corner and Edge Detection for a Locally Angular Model
Alexander Abramenko, Alexander N. Karkishchenko · Pattern Recognition and Image Analysis · 2019
An approach to subpixel corner and edge detection in images is described. The approach is based on algebraic moments of the brightness function describing a halftone image. For an ideal two-dimensional L-corner edge, we consider a model with the following four parameters: the coordinates of the corner vertex, the orientation and the degree measure of the corner, and the brightness values from both sides of the edge. A particular case of the angular model is a linear model that describes a linear edge. To obtain all parameters of the model, six algebraic moments are used. To compute the moments rapidly, masks are used. Based on the angular model, we propose an algorithm that makes it possible to quickly refine the coordinates of the corner and edge points in the image with subpixel accuracy. The use of integral characteristics increases the resistance to various kinds of noises. We perform experiments to confirm the efficiency of the proposed approach.