NDLI: The Research of the ATR System Based on Infrared Images and L-M BP Neural Network

Content Provider	IEEE Xplore Digital Library
Author	Chengpo Mu Jiyuan Wang Zhijie Yuan Xianlei Zhang Chao Han
Copyright Year	2013
Description	Author affiliation: Beijing Inst. of Technol., Beijing, China (Chengpo Mu; Jiyuan Wang; Zhijie Yuan; Xianlei Zhang; Chao Han)
Abstract	With the broad application of information processing technology in the surveillance equipment, the automatic target recognition (ATR) technology has become a key part of the battlefield intelligence processing system. In this paper, we presented an approach for building an ATR system with improved artificial neural network, which can be used to recognize and classify the infrared targets in army field. Because of the invariance of rotation, translation and scaling, we selected the features of Hu invariant moments and roundness as input of the neural network. In order to increase the speed of training, the L-M (Levenberg-Marquardt) algorithm was introduced to improve the traditional BP neural network. The results of simulation show that the approach can meet the requirement of the ATR system in high adaptability and good identification effect.
Starting Page	801
Ending Page	805
File Size	716250
Page Count	5
File Format	PDF
ISBN	9780769550503
DOI	10.1109/ICIG.2013.162
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2013-07-26
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Algorithm design and analysis Training infrared image Image recognition BP neural network Target recognition Hu invariant Feature extraction roundness Biological neural networks ATR system
Content Type	Text
Resource Type	Article

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