Aircraft Visual Identification by Neural Networks

In the present paper, an efficient method for three dimensional aircraftpattern 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 percepiron 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 classifyarbitrary real aircraft images. the results show more than 90% accuracy in ideal conditions and very good robustness in the presence of noise.