saghafi, F., Khansari Zadeh, S. (2629). Aircraft Visual Identification by Neural Networks. Journal of Aerospace Science and Technology, 5(3), 123-128.
fariborz saghafi; Seyed Mohammad Khansari Zadeh. "Aircraft Visual Identification by Neural Networks". Journal of Aerospace Science and Technology, 5, 3, 2629, 123-128.
saghafi, F., Khansari Zadeh, S. (2629). 'Aircraft Visual Identification by Neural Networks', Journal of Aerospace Science and Technology, 5(3), pp. 123-128.
saghafi, F., Khansari Zadeh, S. Aircraft Visual Identification by Neural Networks. Journal of Aerospace Science and Technology, 2629; 5(3): 123-128.
In the present paper, an efficient method for three dimensional aircraft pattern recognition is introduced. In this method, a set of simple area based features extracted from silhouette of aerial vehicles are used to recognize an aircraft type from its optical or infrared images taken by a CCD camera or a FLIR sensor. These images can be taken from any direction and distance relative to the flying aircraft. A multilayer perceptron neural network has been used for the purpose of aircraft classification. The network training has been carried out using a library of images generated by a 3D model of each aircraft. The neural network is successfully trained and used to recognize and classify arbitrary real aircraft images. The results show more than 90% accuracy in ideal conditions and very good robustness in the presence of noise.
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