针对舰船模型其横摆度与纵摆度量的检测问题，研究了一种基于序列图像的复杂背景下字符识别方法用以检测舰船模型的摆度量。首先利用背景图像相邻区域灰度值变化缓慢的特性，采用高斯低通滤波算法对图像背景进行实时更新；其次提出了一种基于差分图像统计信息的自适应阈值分割算法，用以消除光线和环境的变化对背景的影响；最后研究了基于改进扫描线算法与模板匹配算法的字符识别算法。实验结果表明，研究的算法可以在不同光照情况下完整、快速地识别出舰船模型上印刷的字符，完全可以用于摆度量的检测，具有较大的实用价值。

According to inspection problems of horizontal and vertical pendulum amplitude of ship models, a method of character recognition used to inspect pendulum amplitude of ship models based on sequence images in complex background is discussed. Firstly, Gaussian low-pass filtering algorithm is adopted to update image background in real time based on gray value with the characteristic of slow change, which is at the adjacent regions of background images. Secondly, an adaptive threshold segmentation algorithm based on statistical information of difference image is put forward to eliminate the influence of the change of light and environment on background. Finally, character recognition algorithm based on the improved scan line algorithm and template matching algorithm is researched. The experiment results show that the algorithm can identify the characters printed on ship model quickly and completely in the different illumination circumstances. And it can be used to inspect pendulum amplitude. So it has great practical value.