Electricity demand is increasing day by day and hence power utilities are slowly shifting towards renewable energy, mainly solar, as it is more reliable and environment friendly. However, solar power generation systems have very low efficiency and this is the major challenge faced by the researchers. Some of the reasons for the low efficiency is the presence of dust particles, bird droppings, shadows, rain droplets, micro cracks etc. In this article the cracked panel and non-cracked panel can be identified by using complex wavelet transform. The Gaussian filter is used to eliminate the distortions in the cracked panel. And this image can be decomposed by sub band images. The corresponding statistical and texture features can be calculated for sub band images and these features are classified using ANFIS classifier. Finally the segmentation algorithm is used to detect the cracked and non-cracked panel images.