| 结合RSTC不变矩和LVQ神经网络的红外图像目标识别方法 |
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| 引用本文： | 华宇宁,陈赛楠,张乐.结合RSTC不变矩和LVQ神经网络的红外图像目标识别方法[J].沈阳理工大学学报,2013(6):8-11,27. |
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| 作者姓名： | 华宇宁 陈赛楠 张乐 |
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| 作者单位： | 沈阳理工大学信息科学与工程学院,辽宁沈阳110159 |
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| 摘 要： | 通过分析比较红外图像的目标特征,为了达到理想的识别效果,在Maitra不变矩的基础上进行优化,选取RSTC不变矩作为目标识别的特征向量.采用LVQ神经网络建立识别模型,充分发挥神经网络的智能优势.对采集到的红外图像进行了测试实验,结果表明该方法可以提高识别效率.
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| 关 键 词： | 红外图像 目标识别 RSTC不变矩 LVQ神经网络 |
The Target Recognition in Infrared Images Based on the RSTC Invariant Moments and LVQ Neural Network |
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| HUA Yuning;CHEN Sainan;ZHANG Le.The Target Recognition in Infrared Images Based on the RSTC Invariant Moments and LVQ Neural Network[J].Transactions of Shenyang Ligong University,2013(6):8-11,27. |
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| Authors: | HUA Yuning;CHEN Sainan;ZHANG Le |
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| Affiliation: | HUA Yuning;CHEN Sainan;ZHANG Le(Shenyang Ligong University ,Shenyang 110159 ,China) |
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| Abstract: | By analyzing and comparing target characteristics of infrared images,Maitra invariant moments are transformed and optimized to get ideal recognition.RSTC invariant moments are chosen as feature vector for target recognition.LVQ neural network is used to establish recognition model,and it gives full scope to the intelligence advantage of the neural network.The collected infrared images have been tested,and simulation results show that the proposed method is feasible,which can improve the identification rate. |
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| Keywords: | infrared image target recognition RSTC invariant moments LVQ neural network |
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