采用区域生长和EMDs模型的运动目标检测方法

以动态背景中红外运动目标为研究对象,针对二维初级运动检测器在时域上对运动敏感而引起目标运动矢量受背景变化干扰的问题,提出一种结合时域中生物视觉二维初级运动检测器和空域中区域生长方法的运动检测方法。该方法利用时域中二维初级运动检测器检测出运动矢量并将幅值最大的运动矢量作为区域生长的种子点,利用空域中运动目标具有较高红外辐射的图像特性,通过区域生长法,将热辐射特性强于背景的目标分割出来。仿真实验结果表明:该方法在去除背景干扰的同时提取出动态背景中的运动目标,与其他方法相比具有较高的信杂比。

Moving object detection method based on region growing and EMDs model

An infrared moving object detection method which combines Reichardt-type two dimensions Elementary Motion Detectors inspired by biological vision and region growing method was proposed to solve the two dimensions EMDs' sensitive problem in dynamic scenes. EMDs detected the most intensive motion vector signal in temporal domain which was then used as the seeds of the region growing. Region growing method was applied to make a segmentation of the target by its infrared radiation characteristic much different from background in spatial domain. The simulation illustrates that, combing the EMDs in temporal domain with the region growing method in spatial domain achieves much better detection performance in infrared frames than the original Reichardt's model. Compared with other methods, the proposed method could achieve a higher SCR.