POLYHEDRAL OBJECT RECOGNITION BY INDEXING

In computer vision, the indexing problem is the problem of recognizing a few objects in a large database of objects while avoiding the help of the classical image-feature-to-object-feature matching paradigm. In this paper we address the problem of recognizing three-dimensional (3 -D) polyhedral objects from 2-D images by indexing. Both the objects t o be recognized and the images are represented by weighted graphs. The indexing problem is therefore the problem of determining whether a gr aph extracted from the image is present or absent in a database of mod el graphs. We introduce a novel method for performing this graph index ing process which is based both on polynomial characterization of bina ry and weighted graphs and on hashing. We describe in detail this poly nomial characterization and then we show how it can be used in the con text of polyhedral object recognition. Next we describe a practical re cognition-by-indexing system that includes the organization of the dat abase, the representation of polyhedral objects in terms of 2-D charac teristic views, the representation of this views in terms of weighted graphs and the associated image processing. Finally, some experimental results allow the evaluation of the system performance.