Knowledge-based pattern recognition using an associative processor

Arun D. Kulkarni; Vijay B. Nagpurkar

doi:10.1117/12.143064

20 April 1993 Knowledge-based pattern recognition using an associative processor

Arun D. Kulkarni, Vijay B. Nagpurkar

Proceedings Volume 1827, Model-Based Vision; (1993) https://doi.org/10.1117/12.143064
Event: Applications in Optical Science and Engineering, 1992, Boston, MA, United States

Abstract

An image understanding system often consists of the preprocessing, feature extraction, and classification stages. In this paper we have considered a descriptive approach for the classification. As an illustration, we have considered the problem of identification of sailing crafts. The properties like the position of the mast(s), height of the mast, and type of sails are used as features. The classification scheme is described by a hierarchical tree structure. We have created the knowledge base for the classifier by encoding the classification rules, using an associative processor. A number of operations can be performed with the associative processor. They include: an upward closure, downward closure, union, and intersection. In order to use the processor as a classifier, the intersection has been used. The intersection is achieved by performing a downward closure followed by thresholding. We have used a two- layer nonlinear feedback network as the associative processor. We have also developed a menu-driven input/output interface for the classifier.

Citation Download Citation

Arun D. Kulkarni and Vijay B. Nagpurkar "Knowledge-based pattern recognition using an associative processor", Proc. SPIE 1827, Model-Based Vision, (20 April 1993); https://doi.org/10.1117/12.143064

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