Segmentation of solid objects using global and local edge coincidence

Segmentation of monochrome images to obtain boundaries of the object is an important problem in scene analysis. The purpose of this paper is to describe an algorithm for locating object boundaries from an image of objects. The algorithm, called Global-Local-Edge-Coincidence (GLEC) uses both local and global edge information to select a stable set of object boundaries. Significantly improved results are shown in several examples including blocks, building and aerial photograph. The significance of this algorithm is that the boundaries of objects can often be located from a single image.