This paper integrates image recognition and semantic segmentation techniques into a dual-task deep learning model. A key innovation is the incorporation of physical characteristics of ice-covered transmission lines to physically constrain and refine the deep learning outputs. This framework not only achieves accurate identification of ice types on transmission lines but also significantly improves the computational accuracy of ice thickness estimation.