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Background extraction and update method based on histogram in YCbCr color space

机译:基于YCBCR颜色空间直方图的背景提取和更新方法

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In computer vision-based Intelligent Transportation Systems (ITS), one of the key techniques is to exactly detect the vehicles. The common way for vehicle detection is the background difference method. In this paper, we introduce several background extraction and updating methods and develop a new background extraction and update method based on histogram in YCbCr color space. By using YCbCr color space, the influence of illumination change and shadows is reduced. To solve the problem with change in background itself, we propose a background update method by using the pixel change count and histogram. Experiment results show that the proposed algorithm can effectively extract and update the background information in complex traffic environment.
机译:在基于计算机视觉的智能交通系统(其)中,其中一个关键技术是恰好检测车辆。 车辆检测的常见方法是背景差异方法。 在本文中,我们介绍了几个背景提取和更新方法,并基于YCBCR颜色空间中的直方图开发了一种新的背景提取和更新方法。 通过使用YCBCR颜色空间,减少了照明变化和阴影的影响。 为了解决背景本身的变化问题,我们通过使用像素改变计数和直方图提出了背景更新方法。 实验结果表明,该算法可以有效地提取和更新复杂流量环境中的背景信息。

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