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Calculation of Aircraft Area on Satellite Images by Genetic Algorithm
Author(s) -
A.R. Iskhakov,
R. Malikov
Publication year - 2016
Publication title -
bulletin of the south ural state university series mathematical modelling programming and computer software
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.338
H-Index - 11
eISSN - 2308-0256
pISSN - 2071-0216
DOI - 10.14529/mmp160414
Subject(s) - satellite , genetic algorithm , computer science , algorithm , remote sensing , computer vision , aerospace engineering , geology , engineering , machine learning
Classical genetic algorithm is used in a computational experiment, which is described in this article, to measure an area of the aircraft Boeing 737-300. Satellite images containing objects of interest are selected as initial data. The computational experiment consists of two steps. The rst step presents the generalized formulas of values. These formulas are needed to select initial images, using the theory of modi ed descriptive algebra of images. After that, the initial data is formed according to the calculated values, i.e. the satellite image is chosen in the needed scale and the shooting angle. At the second step, a model of technical vision system (computer vision system) in the modi ed descriptive images algebra and a tness function for the genetic algorithm are developed. Then varying parameters of the model are chosen and their optimization is carried out in MATLAB. The article demonstrates development of the model due to its complexity by additional imaging techniques. Experimentally it was found that the evolution of the model improves optimization results.

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