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

Muhammet Ozbay, M. C. Sahingil
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引用次数: 10

Abstract

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.
一种快速、鲁棒的红外图像小目标自动检测算法
红外图像中的目标自动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检率直接影响系统中后续算法的性能,也直接影响系统的总体性能。本文提出了一种快速、鲁棒的红外场景小目标检测算法。采用顶帽变换和均值滤波来提高目标的可见性,并引入两层阈值算法来更准确地计算目标尺寸。最后,利用后处理方法对小目标进行提取。
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