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Proceedings Paper

Novel approach to aircraft silhouette recognition using genetic algorithms
Author(s): Harley R. Myler; Arthur Robert Weeks; Jill Laura Hooper-Giles
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Paper Abstract

An approach to aircraft silhouette recognition using a genetic algorithm for pattern analysis and search tasks and a bimorph shape classifier is presented. The bimorph classifier produces an assortment of shapes derived from a medial axis transform language (MAT) by establishing a set of genes, a chromosome, that portrays the genetic makeup of each shape produced. Each gene represents a unique shape feature for that object and each chromosome a unique object. The chromosomes are used to generate the shapes embodying the classification space. The genetic algorithm then performs a search on the space until the exemplar shape is found that matches an unknown aircraft. The outcome of the search is a chromosome that constitutes the aircraft shape characteristics. The chromosome may then be compared to that of known aircraft to determine the type of aircraft in question. The procedures and results of utilizing this classification system on various aircraft silhouettes are presented.

Paper Details

Date Published: 9 July 1992
PDF: 8 pages
Proc. SPIE 1699, Signal Processing, Sensor Fusion, and Target Recognition, (9 July 1992); doi: 10.1117/12.138222
Show Author Affiliations
Harley R. Myler, Univ. of Central Florida (United States)
Arthur Robert Weeks, Univ. of Central Florida (United States)
Jill Laura Hooper-Giles, Lockheed Space Operations Co. (United States)


Published in SPIE Proceedings Vol. 1699:
Signal Processing, Sensor Fusion, and Target Recognition
Vibeke Libby; Ivan Kadar, Editor(s)

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