Object recognition using local-global graphs

This paper presents a methodology for object recognition using the local-global (L-G) graph approach. In particular, the L-G graph approach based on an image segmentation approach and synthesis of the regions that compose an object. The synthesis of regions is based on the L-G modeling that compares a set of L-G based object models sitting in an L-G Database. The methodology accurate for objects existed in the DB and it has the ability of "learning". Illustrative examples are also provided.