光学学报, 2016, 36 (6): 0615001, 网络出版: 2016-06-06   

基于改进视觉背景提取的运动目标检测算法 下载: 826次

Moving Object Detection Algorithm Based on Improved Visual Background Extractor
作者单位
1 国防科学技术大学电子科学与工程学院, 湖南 长沙 410073
2 中国人民解放军61541部队, 北京 100094
摘要
针对视觉背景提取算法(ViBe)中出现的鬼影问题、不能很好适应背景高频扰动和摄像机抖动问题以及由于采用空间邻域扩散机制引起背景更新错误问题,提出一种改进的视觉背景提取算法。该算法结合视觉显著性判断背景模型中存在的鬼影目标,通过判断背景模型中每个像素点的鬼影程度,结合模糊准则自适应改变时间子采样因子,加快消除鬼影的速度;通过建立一个闪烁程度矩阵,判断背景高频扰动程度来设置自适应匹配阈值,加入小目标丢弃和空洞填充策略;统计前景像素24邻域区域的像素点个数,判断前景像素点是否为摄像机抖动或者背景更新错误引起的噪点,提高算法的稳健性。结果表明,改进后的算法可以很好地弥补经典ViBe算法的不足,准确率与识别率等指标均大大提升。
Abstract
Aiming at the problems of ghost, background turbulence in high frequency, camera jitter and error of background update caused by spatial propagation technique in classic visual background extractor(ViBe) algorithm, an improved ViBe algorithm is proposed. Combined with visual saliency, the new method determines whether the ghost target exists in the background model or not, and adaptively changes the time subsampling factor through the level of ghost for each pixel in the background model, which can improve the rate of ghost elimination. Self-adaptive threshold is adopted in the process of model matching by establishing a blinking degree matrix to judge the high-frequency disturbance level of background, so that the background model is better suitable for the dynamic background. Small object discard and hole filling strategies are added to the new method. It can judge if a foreground pixel is a noise point caused by camera jitter or an error of background update by counting pixel numbers in 24-connected neighboring region of foreground pixels. Therefore, it can improve the robustness of the algorithm. Experiments demonstrate that the improved algorithm is a good way to make up for the deficiency of the original ViBe algorithm. The accuracy and recognition rate are improved greatly.

莫邵文, 邓新蒲, 王帅, 江丹, 祝周鹏. 基于改进视觉背景提取的运动目标检测算法[J]. 光学学报, 2016, 36(6): 0615001. Mo Shaowen, Deng Xinpu, Wang Shuai, Jiang Dan, Zhu Zhoupeng. Moving Object Detection Algorithm Based on Improved Visual Background Extractor[J]. Acta Optica Sinica, 2016, 36(6): 0615001.

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