摘要
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。
Visual Background Extractor(ViBe) is a popular moving object detection 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 improve ViBe algorithm in gray space,which does not effectively use the color information of the image.Related 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 ViBe 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 according to the influence of local changes in luminance and color spatial frequency to human visual system.Then,the algorithm makes use of space consistency of neighborhood pixels to correct the result of pixel classification.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 extracted movement area more complete than the original ViBe algorithm both in indoor and outdoor environments.
作者
彭志勇
刘子琪
窦慧
郭智勇
PENG Zhi-yong;LIU Zi-qi;DOU Hui;GUO Zhi-yong(The 28th Research Institute of China Electronics Technology Group Corporation,Nanjing 210007,China)
出处
《光电子．激光》
EI
CAS
CSCD
北大核心
2019年第5期529-535,共7页
Journal of Optoelectronics·Laser
