Intelligent shape recognition for complex industrial tasks

A knowledge-based shape representation and recognition system that can handle a large class of objects under less constrained situations than required for current machine vision system is proposed. Intelligent integration of different shape representation schemes and generation of the best shape recognition strategy are carried out using global shape properties. The proposed scheme effectively incorporates model-driven top-down and data-driven bottom-up approaches of shape analysis. By analyzing global shape properties, the essential features and their degrees of importance are determined quickly. In the representation phase, objects are described by using these essential features; in the recognition phase, the search for the best candidate is restricted to the models represented by these features, and the observed shape is matched to the candidate models in order of importance of the essential features. Systems are being developed for 2D and 3D shapes separately since they exploit different visual data, i.e. photometric and range, respectively.<>