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Shadow detecting algorithms research for moving objects base on self-adaptive background

机译:基于自适应背景的运动物体阴影检测算法研究

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摘要

The main difficulties in intelligent video monitor is how to detect and eliminate the shadow in the scene. It uses an improved detecting algorithm which is based on self-adaptive background to detect the position and the shape of objects. Then according to the shadow's characters such as the color variation and the structure, two shadow detection algorithms which respectively based on the RGB color model and the HSV color model are introduced. In simulation experiment, the two shadow detection algorithms are analyzed on the shadow detection rate, the shadow discriminating rate, the complexity and the real-time capability, and made the comparison with them. The results of experiment show that the shadow detection algorithms are adaptive and favourable effect on detecting shadow, and can be applied on different fields according to their advantages and disadvantages.
机译:智能视频监视器的主要困难在于如何检测和消除场景中的阴影。它使用一种基于自适应背景的改进的检测算法来检测物体的位置和形状。然后根据阴影的颜色变化和结构特点,介绍了两种分别基于RGB颜色模型和HSV颜色模型的阴影检测算法。在仿真实验中,分析了两种阴影检测算法的阴影检测率,阴影鉴别率,复杂度和实时性,并与之进行比较。实验结果表明,该阴影检测算法具有较好的自适应性和良好的阴影检测效果,可以根据各自的优缺点应用于不同领域。

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