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An Automatic Target Detection Post-Processing Algorithm Based on Swarm Intelligence

机译:基于群体智能的目标自动检测后处理算法

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Presently, most target detection post-processing algorithms are short of self-adapting, which make them have many limitations in automatic target detection from the digital images. Therefore this paper provides a new type of automatic target detection post-processing algorithm (CASI) which adopts clustering algorithm based on swarm intelligence to post-process the detected target pixels. Because of the characteristics of self-organization, robustness, expandability and simplicity, CASI can self-adaptively restore the target pixels, divide them into different targets and delete the false alarm targets. Experimental results conform that the target detection post-processing effect of this new type of algorithm is much better than the ones of morphological transformation in common use.
机译:当前,大多数目标检测后处理算法缺乏自适应性,这使得它们在从数字图像进行自动目标检测方面具有许多局限性。因此,本文提供了一种新型的自动目标检测后处理算法(CASI),该算法采用基于群体智能的聚类算法对检测出的目标像素进行后处理。由于具有自组织,鲁棒性,可扩展性和简单性的特点,CASI可以自适应地恢复目标像素,将其划分为不同的目标并删除虚警目标。实验结果表明,这种新型算法的目标检测后处理效果比常用的形态学变换要好得多。

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