AIRCRAFT CLASSIFICATION USING IMAGE PROCESSING TECHNIQUES AND ARTIFICIAL NEURAL NETWORKS

被引：5

作者：

Karacor, Adil Gursel ^{[1
]}

Torun, Erdal ^{[2
]}

Abay, Rasit ^{[3
]}

机构：

[1] Turkish AF Command, Cent Facil Dept, TR-06100 Ankara, Turkey

[2] Minist Natl Def, R&D Dept, TR-06100 Ankara, Turkey

[3] TUAF Acad, Dept Comp Engn, TR-34809 Istanbul, Turkey

来源：

INTERNATIONAL JOURNAL OF PATTERN RECOGNITION AND ARTIFICIAL INTELLIGENCE | 2011年 / 25卷 / 08期

关键词：

Aircraft classification; image processing; artificial neural network;

D O I：

10.1142/S0218001411009044

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Identifying the type of an approaching aircraft, should it be a helicopter, a fighter jet or a passenger plane, is an important task in both military and civilian practices. The task in question is normally done by using radar or RF signals. In this study, we suggest an alternative method that introduces the use of a still image instead of RF or radar data. The image was transformed to a binary black and white image, using a Matlab script which utilizes Image Processing Toolbox commands of Matlab, in order to extract the necessary features. The extracted image data of four differerent types of aircraft was fed into a three-layered feed forward artificial neural network for classification. Satisfactory results were achieved as the rate of successful classification turned out to be 97% on average.

引用

页码：1321 / 1335

页数：15

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