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Proceedings Paper

Hybrid image recognition architecture
Author(s): Claudio Delrieux; Roman Katz
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Paper Abstract

Current research on artificial vision and pattern recognition tends to concentrate either on numerical processing (filtering, morphological, spectral) or in symbolic or subsymbolic processing (neural networks, fuzzy logic, knowledge-based systems). In this work we combine both kinds of processing in a hybrid image processing architecture. The numerical processing part implements the most usual facilities (equalization, convolution filters, morphological filters, segmentation and description) in a way adequate to transform the input image into a polygonal outline. Then recognition is performed with a rule-based system implemented in Prolog. This allows a neat high-level representation of the patterns to recognize as a set of logical relations (predicates), and also the recognition procedure is represented as a set of logical rules. To integrate the numerical and logical components of our system, we embedded a Prolog interpreter as a software component within a visual programming language. Thus, our architecture features both the speed and versatility of a visual language application, and the abstraction level and modularity of a logical description.

Paper Details

Date Published: 7 June 2002
PDF: 8 pages
Proc. SPIE 4735, Hybrid Image and Signal Processing VIII, (7 June 2002); doi: 10.1117/12.470103
Show Author Affiliations
Claudio Delrieux, Univ. Nacional del Sur (Argentina)
Roman Katz, Univ. Nacional del Sur (Argentina)

Published in SPIE Proceedings Vol. 4735:
Hybrid Image and Signal Processing VIII
David P. Casasent; Andrew G. Tescher, Editor(s)

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