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

机译:基于多分类机决策级别融合的三种颜色IR成像系统的目标识别

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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:针对两个颜色IR成像系统的自动目标识别(ATR)的问题,呈现了一种基于多分类器决策级别融合的IR双频图像目标识别方法。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分类器中,以获得目标图像的似然比根据这些分类器的输出到每个类中;然后,使用可转换的信仰模型(TBM)理论融合这些分类器的输出,以获得目标的判定概率分布属于整个系统的这些不同的类;最后,分析并根据决策规则分析决策概率分布,以获得目标图像的最终识别结果。本文末尾的这些实验结果表明了呈现的方法的有效性。

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