真实场景下视频运动目标自动提取方法

视频运动目标跟踪逐渐成为研究热点并应用到军事民用等领域,为了能够从真实场景中快速准确地提取视频跟踪单运动目标或多运动目标,提出了一种新的运动目标自动提取方法。首先通过自适应阈值获得滤波后的相邻帧差值图像。其次,为了消除差值图像中噪声的影响,标记此二值图像的连通像素来检测出运动目标所在的区域,并与边缘检测出的空间信息结果比较得到运动目标模型。最后,将图像分成若干区域,在每个分区域内依次连接每个运动目标模型的最外围轮廓点,由此构成目标闭合轮廓。利用得到的连续边界,对运动目标进行提取。实验结果表明,该算法能够有效地自动提取速度不同的单运动目标,同时能够提取多运动目标。

Video Moving Object Auto-Extraction in Real Scene

Video moving object tracking technology gradually becomes the study issue and gets wide applications in the military and civil fields etc.To extract video moving objects accurately and rapidly from the real scene,a novel method for auto-extraction is proposed.First,the adaptive threshold is used to get difference image between two adjacent filtered frames.And then,to reduce the influence of noise,the connected components of the binary image are labeled to determine the region of the moving object,and by comparing it with the spatial information by edge detection,the moving object model is initialized.Finally,the image is devided into several regions.The outer pixels of the model boundary are connected respectively and the close contours is finished.Then with the closed contours,the moving object is extracted.The experimental results show that the proposed algorithm can extract the single moving target with different speed and automatically as well as moving multi-targets.