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.