Automatic recognition of isolated or occluded planar objects by a two steps processing

As an application of robot vision to automatic recognition of industriel parts, we present a method which is capable of recognizing isolated or partially occluded two-dimensional objects. Starting from contour following, global features are measured and compared to stored data in order to make a preselection of the models. In the case of isolated object, the preselection leads to an immediate identification of objects. Otherwise, overlapping boundaries are detected and used to accomplish the recognition of occluded objects. By the combination of overlapping boundaries and the object´s contour, a sequential segmentation algorithm is applied to find the complete contour of no hidden objects. As soon as we have obtained the complete contour of an object, we can use once again the global features to perform identification processing. This method has the advantage of being simple,rapide and efficient. Il works well even when the number of objects to be recognized is large.