A new algorithm of real-time detection for infrared motion small targets in rotational and complex background is proposed for solving the problems of high error rate of detection and poor real-time performance. The algorithm, at the first, processes the original infrared image with median filter, calculates the optical flows field, extracts the image's feature points, estimates the background optical flows field, and then extracts the assemblage of the target feature points by setting the threshold. Finally, according to the optical flow vector angle of feature points, target gray interval and the area of feature points of edge detection, the background features points are removed from the assemblage, and thus the infrared motion small targets in rotational and complex background are detected accurately and timely. The experimental results show that the rate of detection of infrared motion small targets reaches 93.8%, the rate of average false alarm is 0.126 times per frame, the average time of target detection per frame is 15.53 milliseconds, and the maximum processing time for each frame is 20.45 milliseconds. It is concluded that the proposed algorithm meets the requirements of real-time moving target detection.%针对旋转复杂背景中红外运动小目标检测误检率高、实时性差等问题,提出了目标检测新算法.首先对图像进行中值滤波预处理,计算图像光流场,提取特征点,估算背景光流;然后设置阈值,判断提取备选目标特征点集合;最后通过特征点光流矢量角度、目标灰度值区间、目标特征点区域边缘检测的方法,排除备选目标特征点集合中的背景特征点,实时准确检测旋转复杂背景中红外运动小目标.实验结果表明,该算法能够准确地检测出红外多个运动小目标,检测率93.8%,平均虚警率0.126次/帧,平均每帧耗时15.53 ms,每帧图像处理的最大时间为20.45 ms,能够满足运动目标检测对实时性的要求.
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