Investigation on Visual Background Extractor Based on Gray Feature and Adaptive Threshold
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摘要: 针对虚拟背景提取(Visual Background extractor,ViBe)算法在目标检测时容易出现鬼影和运动目标阴影的缺点，该文提出了一种基于灰度特征和自适应阈值的ViBe背景建模改进方法。该算法首先利用ViBe算法进行背景建模，得到前景目标，然后对前景目标进行灰度特征判断和自适应阈值比较，得到没有鬼影和运动目标阴影的运动目标。实验结果表明，改进后的算法可以很好地弥补ViBe算法的不足，提高ViBe算法的识别准确率。Abstract: In order to solve the problem of the ghost and the shadow of moving object, an improved Visual Background extractor (ViBe) algorithm is proposed based on gray feature and adaptive threshold. The new method firstly applies the ViBe algorithm to obtain the foreground object, and then uses the gray feature judgment, as well as the adaptive threshold comparison in the foreground object to get the moving object without the ghost and the shadow. Experiments show that the improved algorithm results in better recognition accuracy.
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