Abstract: The changes of indoor illumination and background are not so complex as outdoors.However，their disturbance can also influence the detection of moving objects greatly.This paper analyzed the influence of different illumination conditions and background changes to the moving-object detection in detail.Therefore，it proposed a new hybrid moving-object detection algorithm that could adapt indoor environment changes rapidly.With the illumination information processing as former procedure，this algorithm combined the merits of background subtraction method and symmetrical differencing method.Thus it has much robust to the changing of indoor environment.The experimental results verified the real-time and reliability of the algorithm.

摘要： 室内环境中光照、背景等变化虽然不如外界自然环境那么复杂，但是它们对于运动物体的检测也将产生显著影响。归类分析了室内照明条件与背景变化的不同类型，以及它们对于运动目标检测的影响，在此基础上提出一种能够较好适应室内环境变化的运动目标检测混合算法。该算法结合了帧间差分与背景模型算法的优点，同时引入亮度信息进行前序的处理；因此算法针对不同室内环境都具有较高的鲁棒性。通过仿真实验，证明了该算法的实时性与可靠性。