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Proceedings Paper

Expert system for identification of objects within remotely sensed images
Author(s): Ahmed M. Nazif; Ragab A. Aboelenine
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Paper Abstract

This paper presents a high level vision expert system designed to identify objects found in 2-D vertically photographed images. The goal of the system is to identify the image contents by assigning interpretations to detected objects. The system assumes that the objects have already been detected by a low level vision system. Each object's location and boundaries are then identified. The interpretation process starts by segmenting the 2-D object into its components. The descriptive features (geometrical features) for each region are then defined. The confidence factors for each feature are anticipated in the object using Bayesian probabilities principles. The relational predicates for the object's model regions are then defined. Finally, the regions knowledge is represented in a frame-like representation. The system uses the object's knowledge and model's knowledge, both represented as frames, to infer the type of the unidentified object. The models are stored in classified databases relating the object's models, confidence values, and features ranges. The inference process matches the object's features to those of the models and generates plausible hypothesis of the models that coarsely identify the object. Forward reasoning is used in the plausible hypothesis phase and backward reasoning is used in the hypothesis verification phase. The system is composed of an analysis part, inference engine, a supervisor, short and long term memories (STM & LTM resp.), and an input/output section.

Paper Details

Date Published: 1 February 1992
PDF: 12 pages
Proc. SPIE 1607, Intelligent Robots and Computer Vision X: Algorithms and Techniques, (1 February 1992); doi: 10.1117/12.57096
Show Author Affiliations
Ahmed M. Nazif, Cairo Univ. (Egypt)
Ragab A. Aboelenine, Cairo Univ. (Egypt)

Published in SPIE Proceedings Vol. 1607:
Intelligent Robots and Computer Vision X: Algorithms and Techniques
David P. Casasent, Editor(s)

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