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The research of the ATR system based on infrared images and L-M BP neural network

  • Chengpo Mu
  • , Jiyuan Wang
  • , Zhijie Yuan
  • , Xianlei Zhang
  • , Chao Han
  • Beijing Institute of Technology

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

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.

Original languageEnglish
Title of host publicationProceedings - 2013 7th International Conference on Image and Graphics, ICIG 2013
Pages801-805
Number of pages5
DOIs
Publication statusPublished - 2013
Event2013 7th International Conference on Image and Graphics, ICIG 2013 - Qingdao, Shandong, China
Duration: 26 Jul 201328 Jul 2013

Publication series

NameProceedings - 2013 7th International Conference on Image and Graphics, ICIG 2013

Conference

Conference2013 7th International Conference on Image and Graphics, ICIG 2013
Country/TerritoryChina
CityQingdao, Shandong
Period26/07/1328/07/13

Keywords

  • ATR system
  • BP neural network
  • Hu invariant
  • Infrared image
  • Roundness

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