提出了一种基于特征点匹配和校验的鲁棒实时电子稳像算法.首先利用Kanade-Lucas-Tomasi角点检测器提取参考帧和当前帧的特征点，并用绝对误差和准则进行特征点匹配；在校验阶段，提出一种能够有效剔除前景运动物体特征点和错误匹配点的空间位置不变准则；最后，在相似运动模型下，利用最小二乘法求解全局运动矢量进行运动补偿.实验证明：该算法满足实时性要求，对视频的平移、旋转、缩放运动都有较好的稳像效果，并对运动物体具有鲁棒性.

A robust real-time electronic image stabilization algorithm was proposed based on feature matching and checking. In the algorithm, feature points in reference and current frame were extracted by Kanade-Lucas-Tomasi corner detector and matched by the sum of absolute difference criterion firstly. In the process of checking, a spatial location invariant criterion was presented to delete those points which were error-matching or appeared in foreground moving objects effectively. Finally, the global motion vector was computed by least-squares algorithm in similarity motion model and applied to compensate. Experimental results show that this algorithm is able to meet the requirement in real time and has good performance to the translation, rotation and zoom, and is robust to foreground moving objects.