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Proceedings Paper

Rule-Based Interpreting Of Aerial Photographs Using LES
Author(s): W. A. Perkins; T. J. Laffey; T. A. Nguyen
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Paper Abstract

Human photo-interpreters use expert knowledge and contextual information to help them analyze a scene. We have experimented with the Lockheed Expert System (LES) to see if contextual information can be useful in interpreting aerial photographs. First, the grey-scale image is segmented into uniform or slowly-varying intensity regions or contiguous textured regions using an edge-based segmentation technique. Next, the system computes a set of attributes for each region. Some of these attributes are based on local properties of that region only (e.g., area, average-intensity, texture-strength, etc.), while others are based on contextual or global information (e.g., adjacent-regions and nearby-regions). Finally, LES is given the task of classifying all the regions using the attribute values. It makes use of multiple goals and multiple rule sets to determine the best classification; regions, which do not satisfy any of the rules, are left unclassified. Unlike programs which use statistical methods, LES uses contextual information such as the fact that cars are likely to be adjacent to roads, which significantly improves its performance on regions which are difficult to classify.

Paper Details

Date Published: 5 April 1985
PDF: 9 pages
Proc. SPIE 0548, Applications of Artificial Intelligence II, (5 April 1985); doi: 10.1117/12.948416
Show Author Affiliations
W. A. Perkins, Lockheed Research and Development Division (United States)
T. J. Laffey, Lockheed Research and Development Division (United States)
T. A. Nguyen, Lockheed Research and Development Division (United States)


Published in SPIE Proceedings Vol. 0548:
Applications of Artificial Intelligence II
John F. Gilmore, Editor(s)

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