Recognition of Coating Corrosion Image of Salt Field Photovoltaic Power Generation Equipment Based on SIFT Algorithm

In view of the problem that the chaotic feature points are difficult to effectively describe the coating corrosion information, resulting in low accuracy and efficiency, a method based on SIFT algorithm to identify the coating corrosion image of photovoltaic power generation equipment in salt fields is studied. The image is grayed to remove color interference and reduce computational complexity. The grayed image is filtered to smooth the image and remove noise, so that the corrosion characteristics of the coating are clearer. The SIFT algorithm is used to extract and transform the key feature points of the coating corrosion image to generate feature descriptors with scale invariance and rotation invariance. These feature descriptors are matched with the descriptors in the feature library of known corrosion images through the matching algorithm to realize the matching recognition of coating corrosion images. The experimental results show that this method performs well in recognizing the coating corrosion image of photovoltaic power generation equipment in salt field, with the highest recognition accuracy and efficiency, and has higher practical value and promotion potential in practical application.