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

机译:暗影检测算法研究自适应背景的移动物体基础

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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是如何检测和消除场景中的阴影。它使用改进的检测算法,该算法基于自适应背景来检测物体的位置和形状。然后根据诸如颜色变化和结构的阴影的字符,引入了分别基于RGB颜色模型和HSV颜色模型的两个阴影检测算法。在仿真实验中,在阴影检测速率下分析了两个阴影检测算法,阴影鉴别率,复杂性和实时能力,并与它们进行了比较。实验结果表明,阴影检测算法对检测阴影具有适应性和有利的影响,并且可以根据其优点和缺点在不同的领域应用。

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