The computation of a shape's orientation is a common task in the area of computer vision and image processing, being used for example to define a local frame of reference and is helpful for recognition and registration, robot manipulation, etc. It is usually an initial step or a part of data preprocessing in many image processing and computer vision tasks. Thus, it is important to have a good solution for shape orientation because an unsuitable solution could lead to a big cumulative error at the end of the computing process. There are several approaches to the problem--most of them could be understood as the `area based' ones, or at least they do not take into account all the boundary points (if a shape orientation measure is based on its encasing rectangle, only the convex hull points count, for example). Thus, the demand for a pure `boundary based' method, where the orientation of the shape is dependent on the boundary points seems to be very reasonable. Such a metho...
Jovisa D. Zunic, Milos Stojmenovic