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中文摘要：
井下危险区域中运动目标检测和跟踪在井下安全监控系统中有着重要作用，可以做到提前预警，通过结合联动系统防止危险事故发生。对于光线缓慢变化和突然变化的环境下的移动目标，分别提出用结合帧差法的改进的在线调节学习速率混合高斯模型和结合颜色梯度以及数学形态学的背景建模方法进行检测，并通过HSV颜色模型有效去除了阴影，从而快速准确定位运动目标。
英文摘要：
Detecting and tracking moving objects in the dangerous area of underground mine plays an important part in coal mine monitoring system, which can issue early warning and prevent dangerous accidents in combination with an interlocking system. For the objects moving in environment with slowly changing or suddenly changing illumination, it is proposed to realize the detection by an improved on-line adaptive learning rate Gaussian mixture model in combination with frame difference, and the background modeling method in combination with color gradient and mathematical morphology, and to remove the shadow by HSV color model, thus enabling a rapid and accurate location of moving object.
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