一种基于轮廓与背景消除的红外视频移动目标检测方案

An infrared video moving target detection scheme based on outline and background elimination

针对红外视频的移动目标检测算法在还原目标时,目标的轮廓还原准确率较低的问题,提出一种基于轮廓与背景消除的红外视频移动目标检测方案。首先,从视频中选取一些不含目标对象的帧,对选取的帧进行统计处理并建立背景帧;分析背景的场景变化建立变化的自适应背景帧,并将背景帧的杂波过滤掉;然后,使用Canny边缘检测和K-means聚类检测目标轮廓并将目标轮廓从背景提取出来;使用形态学的边缘连通算法将目标轮廓进行关闭与Flood-fill填充处理获得目标对象的形状。对比实验结果证明,相较于其他红外视频移动目标检测算法,该算法获得了较好的目标轮廓与形状,同时,该算法的检测率与虚警率性能以及每帧的处理时间均较优。

Aiming at the problem of low accuracy rate of target outline restoration when the detection algorithm of moving target in infrared video is used to restore the target,a new detection scheme of moving target in the infrared video is proposed,which is based on outline and background elimination. The steps of the scheme are：the frames which do not contain the target are selected,the statistical processing is conducted for the selected frames,the background frame is constructed,the change of the background scene is analyzed,the adaptive background frame with changing scene is built,the clutter in the background frame is filtered,Canny edge detector and K-means clustering approach are used to extract the target outline from the background,and the morphological edge linking algorithm is adopted to close target outlines and Flood-fill is used to get the target silhouettes. The results of the contrast experiment prove that,compared with the other algorithms in the same category,the proposed algorithm can get better target outline and shape,has higher detection rate and lower false alarm,and spends shorter processing time for every frame.