基于自适应Lab色差阈值的ViBe运动目标检测算法

针对视觉背景提取算法(ViBe)对光照变化和运动 阴影敏感、提取的运动区域容易产生空洞的问题,本文提出了基于自 适应Lab色差阈值的ViBe运动目标检测算法。根据图像的局部背景亮度与色彩的空间频率对 人眼视觉的影响,自适应的确定 每个像素点的色差阈值,用于像素点与背景模型的匹配；然后,利用邻域像素点的空间一致 性原则,对检测结果进行修正； 最后,统计各连通域的面积,去除小面积的运动目标。实验结果表明,本算法可以有效的适 应光照变化、抑制运动阴影、填 补运动区域的空洞,具有比ViBe算法更好的检测效果。

ViBe algorithm for moving object detection based on adaptive Lab color differenc e threshold

Visual Background Extractor (ViBe) is a popular moving object detectio n algorithm,which has a high efficiency and a good detection effect.However,ViBe algorithm is sensitive to illumination changes and motion shadows and extracts movement area incompletely.At present,most researchers im prove ViBe algorithm in gray space,which does not effectively use the color information of the image.Relate d research shows that the moving object detection algorithm based on Lab color space has higher recognition rate and lower false detection rate. Therefore,this paper studies ViBe algorithm in Lab color space and proposes a V iBe moving object detection algorithm based on adaptive Lab color difference threshold.For matching pixels with background model,the algorithm adaptively determines color difference threshold of each pixel accordi ng to the influence of local changes in luminance and color spatial frequency to human visual system.Then,t he algorithm makes use of space consistency of neighborhood pixels to correct the result of pixel classifi cation.Finally,it counts pixel numbers of all connecting areas to remove small moving objects.Experiments show that the algorithm proposed is less sensitive to illumination changes and motion shadows,and makes extracte d movement area more complete than the original ViBe algorithm both in indoor and outdoor environment s.