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A fast and robust automatic object detection algorithm to detect small objects in infrared images

机译:一种快速稳健的自动对象检测算法,用于检测红外图像中的小对象

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摘要

Automatic object detection in infrared images is a vital task for many military defense systems. The high detection rate and low false detection rate of this phase directly affect the performance of the following algorithms in the system as well as the general performance of the system. In this work, a fast and robust algorithm is proposed for detection of small and high intensity objects in infrared scenes. Top-hat transformation and mean filter was used to increase the visibility of the objects, and a two-layer thresholding algorithm was introduced to calculate the object sizes more accurately. Finally, small objects extracted by using post processing methods.
机译:红外图像中的自动对象检测是许多军事防御系统的重要任务。该阶段的高检测率和低误报率直接影响系统中以下算法的性能以及系统的一般性能。在这项工作中,提出了一种快速且稳健的算法,用于检测红外场景中的小型和高强度对象。顶帽变换和平均滤波器用于增加对象的可见性,并引入双层阈值算法以更准确地计算物体尺寸。最后,使用后处理方法提取的小物体。

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