Background subtraction is an example of a moving object detection technique that uses machine vision systems. Conventional moving object detection methods need complicated thresholds for background modeling to address changes in illumination. This paper proposes a novel background modeling approach without thresholding based on a bit-planes method, which fully utilizes color characteristics through spatial and temporal-based improvement. The proposed idea is effective and efficiently solving for shadow disturbance and brightness changes. We evaluate our proposed method using several challenging indoor and outdoor sequences from the CDNET 2014 dataset. The experiments show that the proposed idea typically achieves a higher rate of detection accuracy than those of the current state-of-the-art approaches.

中文翻译：

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通过无阈值的图像位平面表示进行移动对象检测

背景减法是使用机器视觉系统的运动物体检测技术的一个例子。传统的运动物体检测方法需要复杂的背景建模阈值来解决光照变化。本文提出了一种基于位平面方法的无阈值的新型背景建模方法，该方法通过基于空间和时间的改进充分利用颜色特征。所提出的想法有效且高效地解决了阴影干扰和亮度变化。我们使用 CDNET 2014 数据集中的几个具有挑战性的室内和室外序列来评估我们提出的方法。实验表明，所提出的想法通常比当前最先进的方法实现更高的检测准确率。