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A modified motion detection algorithm in complex background

机译:复杂背景下的一种改进的运动检测算法

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摘要

Indoor and outdoor real-time monitoring of scenes has become a hot topic for decades. This paper analyzes the median filter and its shortcomings and proposes a modified detection method for moving objects with complex background. Using the method based on decision-making data gives the weights of a consecutive sequence of frames to calculate the weighted average of the corresponding values of pixel in them and the background is modeled for real-time updating. Besides, the thrice threshold processing used to detect and extract objects is presented, which is by using a combination of standard deviation in weighted algorithm and the adaptive threshold algorithm. The experiment results indicate that adopting this method can separate the object from the background and remove the background mistaken for objects and meet the system's realtime requirements of monitoring.
机译:数十年来,室内和室外场景的实时监控已成为热门话题。本文分析了中值滤波器的缺点,提出了一种对背景复杂的运动物体进行改进的检测方法。使用基于决策数据的方法,可以给出连续帧序列的权重,以计算帧中相应像素值的加权平均值,并对背景进行建模以进行实时更新。此外,提出了三次阈值处理方法,该方法通过结合加权算法中的标准差和自适应阈值算法来进行物体的检测和提取。实验结果表明,采用该方法可以将物体与背景分离,消除误认为物体的背景,满足系统实时监控的要求。

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