Research of the ATR system based on the 3-D models and L-M BP neural network

Cheng Po Mu*, Zhi Jie Yuan, Ji Yuan Wang, Yuan Qian Chen, Qing Xian Dong

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

1 Citation (Scopus)

Abstract

Automatic target recognition (ATR) is an important issue for military applications, the topic of the ATR system belongs to the field of pattern recognition and classification. In the paper, we present an approach for building an ATR system with improved artificial neural network to recognize and classify the typical targets in the battle field. The invariant features of Hu invariant moments and roundness were selected to be the inputs of the neural network because they have the invariances of rotation, translation and scaling. The pictures of the targets are generated by the 3-D models to improve the recognition rate because it is necessary to provide enough pictures for training the artificial neural network. The simulations prove that the approach can be implement ed in the ATR system and it has a high recognition rate and can be applied in real time.

Original languageEnglish
Pages (from-to)306-310
Number of pages5
JournalJournal of Beijing Institute of Technology (English Edition)
Volume23
Issue number3
Publication statusPublished - 1 Sept 2014

Keywords

  • 3-D models
  • ATR system
  • BP neural network
  • Hu invariant
  • Pattern recognition
  • Pictures generation
  • Roundness

Fingerprint

Dive into the research topics of 'Research of the ATR system based on the 3-D models and L-M BP neural network'. Together they form a unique fingerprint.

Cite this