基于相似度阈值模糊聚类的红外区域提取方法

针对输电线路电力设备红外图像热故障区域检测，提出采用一种基于相似度阈值的模糊聚类热故障区域提取方法。在该方法中，改进了传统模糊均值聚类算法的迭代求解方式，采用一种阈值化模糊聚类；其次，通过对目标区域局部邻域像素的相似度聚类分析，并结合其隶属度的计算，确保局部邻域像素在聚类上的相似性。同时，引入了最大相似度阈值准则简化均值的设置以及自高向低的迭代方式，从而提升区域提取效率。最后通过真实输电线路电气设备红外故障图像测试，验证了文中所提方法的有效性和适用性。

Infrared Image Segmentation Method Based on Fuzzy Clustering with Similarity Thresholding

This paper presents a fuzzy clustering method based on similarity thresholding to detect an overheating fault region from an infrared image of a transmission line. In this method, the original iteration mechanism of fuzzy clustering was improved and a thresholding fuzzy clustering model was built. Thus, a fuzzy member was utilized to measure the neighboring pixels t by conducting cluster analysis on the object region with local neighboring pixels. This ensured similarity during the clustering of the local neighboring pixels into the cluster center. In addition, the maximum similarity thresholding rule was applied to determine the final thresholding using the strategy of thresholding from top to bottom, thus improving the efficiency of the method in obtaining the final region of interest in the infrared image using fuzzy clustering. Finally, experimental results on infrared images of transmission lines show that the good performance of the proposed method and that the proposed method is suitable for fault detection in transmission lines.