AIRCRAFT VISUAL IDENTIFICATION BY NEURAL NETWORKS

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SAGHAFI F.; KHANSARIZADEH S.M.; ETMINANBAKHSH V.

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Journal: Journal of Aerospace Science and Technology Year:2008 | Volume:5 | Issue:3 Page(s): 123-128

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Title

AIRCRAFT VISUAL IDENTIFICATION BY NEURAL NETWORKS

Author(s)

SAGHAFI F. | KHANSARIZADEH S.M. | ETMINANBAKHSH V. | Issue Writer Certificate

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Abstract

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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APA: Copy

SAGHAFI, F., KHANSARIZADEH, S.M., & ETMINANBAKHSH, V.. (2008). AIRCRAFT VISUAL IDENTIFICATION BY NEURAL NETWORKS. JOURNAL OF AEROSPACE SCIENCE AND TECHNOLOGY (JAST), 5(3), 123-128. SID. https://sid.ir/paper/290987/en

Vancouver: Copy

SAGHAFI F., KHANSARIZADEH S.M., ETMINANBAKHSH V.. AIRCRAFT VISUAL IDENTIFICATION BY NEURAL NETWORKS. JOURNAL OF AEROSPACE SCIENCE AND TECHNOLOGY (JAST)[Internet]. 2008;5(3):123-128. Available from: https://sid.ir/paper/290987/en

IEEE: Copy

F. SAGHAFI, S.M. KHANSARIZADEH, and V. ETMINANBAKHSH, “AIRCRAFT VISUAL IDENTIFICATION BY NEURAL NETWORKS,” JOURNAL OF AEROSPACE SCIENCE AND TECHNOLOGY (JAST), vol. 5, no. 3, pp. 123–128, 2008, [Online]. Available: https://sid.ir/paper/290987/en

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