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A Multiframes Integration Object Detection Algorithm Based on Time-Domain and Space-Domain

机译:基于时域和空域的多帧集成目标检测算法

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摘要

In order to overcome the disadvantages of the commonly used object detection algorithm, this paper proposed a multiframes integration object detection algorithm based on time-domain and space-domain (MFITS). At first, the consecutive multiframes were observed in time-domain. Then the horizontal and vertical four-direction extension neighborhood of each target pixel were selected in space-domain. Transverse and longitudinal sections were formed by fusing of the time-domain and space-domain. The mean and standard deviation of the pixels in transverse and longitudinal section were calculated. We also added an improved median filter to generate a new pixel in each target pixel position, eventually to generate a new image. This method is not only to overcome the RPAC method affected by lights, shadows, and noise, but also to reserve the object information to the maximum compared with the interframe difference method and overcome the difficulty in dealing with the high frequency noise compared with the adaptive background modeling algorithm. The experiment results showed that the proposed algorithm reserved the motion object information well and removed the background to the maximum.
机译:为了克服常用目标检测算法的弊端,提出了一种基于时域和空域(MFITS)的多帧集成目标检测算法。首先,在时域中观察到连续的多帧。然后在空间域中选择每个目标像素的水平和垂直四方向扩展邻域。横向和纵向截面是通过时域和空间域的融合而形成的。计算了横断面和纵断面像素的平均偏差和标准偏差。我们还添加了改进的中值滤波器,以在每个目标像素位置生成一个新像素,最终生成一个新图像。该方法不仅克服了受光照,阴影和噪声影响的RPAC方法,而且与帧间差分方法相比,可以最大程度地保留对象信息,并且与自适应方法相比,克服了处理高频噪声的困难。背景建模算法。实验结果表明,该算法很好地保留了运动对象信息,并且最大限度地消除了背景。

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  • 来源
    《Mathematical Problems in Engineering》 |2018年第2期|4127305.1-4127305.15|共15页
  • 作者单位

    Hebei Agr Univ, Coll Mech & Elect Engn, Baoding 071000, Peoples R China;

    Hebei Agr Univ, Coll Mech & Elect Engn, Baoding 071000, Peoples R China;

    Hebei Agr Univ, Coll Mech & Elect Engn, Baoding 071000, Peoples R China;

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