To enhance the efficiency of astronomical observations, studies on algorithms for recognizing and evaluating the degree of effect of thin clouds on ground-based optical astronomical observations at night are necessary. First, we select images of ground-based wide angle camera array (GWAC), a large field-of-view ground-based optical astronomical equipment, after analyzing the effects of clouds on ground-based optical astronomical observations and traditional ground-based cloud map algorithms. Then, based on the comparison of the GWAC image characteristics, such as gray-scale value distribution, we select the fuzzy C-means clustering (FCM) algorithm to process the GWAC images affected by thin clouds. Next, by repeating multiple sets of experiments, the appropriate key parameters such as the number of clustering layers, the number of iterations, and the smoothing factor are selected using the FCM algorithm. Finally, the FCM algorithm’s results are compared to those of the traditional astronomical star-extinction method. Set the smoothing factor to 1.5 and the number of clustering layers to 5, after 10 cycles of iterative calculations, the FCM algorithm clusters the night sky background into 5 layers.The results of the hierarchical distribution match the cloud thickness distribution estimated via naked eye as well as the results of the accurate traditional astronomical star-extinction method.The FCM algorithm can effectively recognize and analyze the thickness distribution structure of thin clouds in optical astronomical images from large field-of-view ground-based telescopes, allowing it to grade the effect of thin clouds. Using a larger field-of-view fisheye lens and CCD cameras with this FCM algorithm, it is promising to develop an equipment for monitoring the distribution of thin clouds and evaluating the degree of effect in real-time, which would enhance the efficiency of ground-based optical astronomical observations.