基于视频监控的电力设备图像识别

Power equipment image recognition based on video surveillance

为了解决传统模板匹配算法识别电力设备图像速度慢等问题,文中融合了视频监控系统和图像识别系统,提出了一种改进的模板匹配算法。首先,提取四分之一的模板数据在源图像的四分之一范围内进行第一次匹配,并在匹配过程中给出合理的误差阈值。然后,对第一次匹配中最小误差点的邻域进行第二次匹配,得到最终匹配结果。最后,将该算法应用于电力设备的识别和异常状态的检测。实验结果表明,与其它常用的模板匹配算法相比,该匹配算法不仅能准确识别电力设备和检测设备故障,而且提高了识别速度。

In order to solve the problem that the traditional template matching algorithm is slow to recognize the image of power equipment,an improved template matching algorithm is proposed by integrating video surveillance system and image recognition system.Firstly,a quarter of template data is extracted and matched the first time within a quarter of the source image,and a reasonable error threshold is given during the matching process.Then,the neighborhood of the minimum error point in the first matching is matched for the second time,and the final matching result is obtained.Finally,the proposed algorithm is applied to the identification of power equipment and the detection of abnormal state.Experiment results show that compared with other common template matching algorithms,the proposed matching algorithm can not only accurately identify power equipment and detect equipment faults but also improve the recognition speed.