A Model-Constrained Rule-Based Pattern
Matching System for Object Recognition
Yu-Shan Fong and Pamprasad A. Shetty
Department of Electrical and Computer Engineering,
Potsdam, New York 13676
A model-contrained rule-based pattern matching system is considered in this paper. It is based on the concept of interactive hierarchical structures for signal and image understanding . The actual implementation is centered around the ideas of view-angle independent object recognition, and robustness with incomplete or noisy line drawings of objects.
The pattern matching subsystem has a two-level structure. The lower level involves feature extraction and the higher level deals with pattern matching by inferencing. Incomplete line drawings and noisy line drawings are detected and modified by the preprocessing module before being presented to the pattern matcher.
The system implemented has the characteristics of being flexible and easy to modify. These advantages are rooted in the utilization of the rule-based approach. A test of the system has been carried out, and the result is satisfactory.
This work was supported in part by the Naval Research Laboratory under contract N00014-85-E-2421.