In view of the current problem that the railway safety zone division along the electrified railway with complex background needs to use actual fixed standard parts as reference and the division range is small, a smart zone division algorithm that does not require reference objects is proposed. This method first calculates the corresponding GSD parameters based on the relevant parameters in the images collected by the UAV, then uses DeepLabv3+ model with ECA-Net module to accurately segment the railway in the image. Then, a series of image processing operations such as edge detection, opening operation, and probability Hough transform are used to extract the key pixel points that make up the railway, and the least squares algorithm is used to fit the railway and obtain the mathematical expression of the railway. Finally, combined with mathematical algorithms, GSD parameters, and the mathematical expression of the railway, the division of the safety zone is completed. Experimental results show that the measurement accuracy of this method is over 90%, without the need to select fixed reference objects, and has strong adaptability and high robustness, which has high practicality and reliability and provides effective technical support for safety management along the electrified railway.