摘要
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.
源语言 | 英语 |
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页(从-至) | 306-310 |
页数 | 5 |
期刊 | Journal of Beijing Institute of Technology (English Edition) |
卷 | 23 |
期 | 3 |
出版状态 | 已出版 - 1 9月 2014 |