With the development of industrial automation,infrared image recognition technology is applied more frequently to the field of automated production.Infrared images are characterized by high noise,poor image quality and lack of color information.In view of the above characteristics,a detection method,Infrared Image Frequency Domain Detection Method (IFDM),is proposed based on infrared image frequency information to identify infrared images.Firstly,different from traditional image processing,this method starts from the frequency domain and transforms the image information into the frequency domain through discrete Fourier transform,which is beneficial to better grasp the unique structural features of infrared images.Secondly,the learnable screening of frequency information in the frequency domain enhances the feature extraction capability of the model.Finally,the Transformer structure is introduced,which can better fuse the global information in the image than the CNN structure.Three unique infrared image datasets are used to verify the feasibility of the method in comparison with other algorithms in terms of accuracy and model convergence rate.