在电力系统中，利用计算机视觉和图像处理技术对零值绝缘子进行检测，对保障电力系统的安全运行具有非常重要的作用。提出了一种基于红外图像的零值绝缘子自动检测算法。该算法首先对输入图像进行预处理，利用GLOH描述子结合机器学习精确定位绝缘子，然后利用图谱方法提取图像的边界点，并搜索初始轮廓线作为初始值，利用GVF Snake模型检测绝缘子串的精确轮廓线，以分割绝缘子，最后通过分析统计直方图，实现零值绝缘子的自动检测。实验结果表明，所提出的算法可以有效地检测零值绝缘子。

In power systems, to use computer vision and image processing technology to detect zero-value insulators is very important for the safe operation of power systems. An automatic zero-value insulator detection algorithm based on infrared images is proposed. Firstly, an input image is preprocessed and the insulator is positioned precisely by combining the GLOH descriptors with machine learning. Then, the boundary points in the image are extracted by using a graphic method. The initial contour searched is used as the initial value. A GVF Snake model is used to check the precise contour of the insulator string so as to separate the insulators. Finally, automatic zero-value insulator detection is realized by analyzing the statistical histogram. The experimental results show that the proposed algorithm can detect the zero value insulators effectively.