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Perimeter intrusion detection based on improved Surendra background update algorithm

机译:基于改进的Surendra背景更新算法的边界入侵检测

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An improved Surendra background update algorithm for moving targets detection is proposed in this paper, which is beneficial to the background update and can automatically change threshold. Firstly, the initial background frame can be obtained through the arithmetic average to the first few frame images. Secondly, The OTSU method is used for adaptive threshold selection to background updating, so that the moving objects can be obtained by morphological processing. Experiments show that the improved Surendra background updating algorithm can detect the moving targets effectively and overcome the original method's shortcoming which needs to manually intervene the threshold. The impact of such background disturbances and illumination changes to moving targets detection has a good inhibition.
机译:提出了一种改进的Surendra运动目标检测背景更新算法,该算法有益于背景更新并且可以自动改变阈值。首先,可以通过对前几个帧图像进行算术平均获得初始背景帧。其次,采用OTSU方法对背景更新进行自适应阈值选择,从而可以通过形态学处理获得运动物体。实验表明,改进的Surendra背景更新算法可以有效地检测出运动目标,克服了原有方法需要人工干预阈值的缺点。这种背景干扰和照明变化对移动目标检测的影响具有良好的抑制作用。

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