Infrared images have low contrast and low signal-to-noise ratio, which is always a huge challenge for the segmentation of infrared photovoltaic panel images. In order to solve the problem that the traditional Fuzzy C-Means (FCM) clustering algorithm is susceptible to the uncertainty of the initial clustering center and does not consider the spatial information, a clustering algorithm based on FCM is proposed. The algorithm uses the histogram, meanwhile, the characteristics of the graph determine the initial clustering center, and based on the traditional FCM and Fuzzy Kernel C-Means (KFCM) algorithm, the traditional FCM is improved by the relationship between the spatial information among pixels and the neighboring pixels. The objective function is clustered to derive a new objective function. The experimental results show that the proposed algorithm has significantly lower over-segmentation and mis-segmentation rate than the Otsu algorithm, the adaptive k-means algorithm, and KFCM algorithm. The effect is very close to the manual segmentation map.