摘要
在户外交通环境下,采用传统目标检测方法容易产生大量噪声,传统三维最大类间方差(Otsu)方法能消除噪声,但是不能满足实时性。为此,提出一种基于分解的三维Otsu运动车辆检测方法。通过隔帧对称差分法得到2个差分图像,对这2个差分图像采用基于分解的三维Otsu法进行阈值分割,对这2个二值图像在使用数学形态学滤波后,求交集得到运动车辆目标。实验结果表明,该方法在视频帧出现不规则抖动的情况下,能实时和精确地检测出运动车辆。
It is frequent to produce a large number of noise in the outdoor complex traffic environment by traditional object detection method.Traditional three-dimensional Otsu method can eliminate the effect of image noise,but can not satisfy the real-time demand.To solve the above problems,a method for three-dimensional Otsu moving vehicle detection based on decomposition is proposed.Two difference images are got by the method of interval frame symmetry differencing.Two binary images are obtained after using a method based on decomposition three-dimensional Otsu.Moving cars are got by seeking the common ground in these two binary images after filtering with mathematical morphology.Experimental results show that it can detect moving cars for real-time and accuracy in the case of jittering in the video frame.
出处
《计算机工程》
CAS
CSCD
2013年第2期172-177,共6页
Computer Engineering
基金
浙江省自然科学基金资助项目(Y1080533)
关键词
运动目标检测
隔帧对称差分
数学形态学滤波
阈值分割
视频帧
moving object detection
interval frame symmetry difference
mathematical morphology filtering
threshold segmentation
video frame
