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Target recognition for the two color IR imaging system based on the multi-classifiers decision level fusion

机译:基于多分类器决策水平融合的两色红外成像系统目标识别

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Aim at the problem of Automatic Target Recognition (ATR) for the two color IR imaging system, presented a method for the IR dual band image target recognition based on multi-classifiers decision level fusion. This method firstly inputted all kinds of feature vectors of the target image into these relevant classifiers respectively to get the likelihood ratio of the target image fall into every class according to the outputs of these classifiers; Then, fused the outputs of these classifiers using Transformable Belief Model(TBM) theory to get the decision probability distribution of the target belong to these different classes for the whole system; Finally, analyzed and decided the decision probability distribution according to the decision rule to get the final recognition result for the target image. These experimental results at the end of this paper showed the effectiveness of the presented method.
机译:针对两色红外成像系统的自动目标识别(ATR)问题,提出了一种基于多分类器决策水平融合的红外双波段图像目标识别方法。该方法首先将目标图像的各种特征向量分别输入到这些相关的分类器中,以根据这些分类器的输出得到目标图像的似然比落入各个类别。然后,利用可变换信念模型理论将这些分类器的输出融合在一起,得出整个系统中属于这些不同类别的目标的决策概率分布。最后,根据决策规则对决策概率分布进行分析和确定,以获得目标图像的最终识别结果。本文结尾处的这些实验结果表明了该方法的有效性。

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