Abstract: To address the problems of low efficiency and insufficient accuracy in manually compiling wiring tables based on engineering drawings during the construction and maintenance of railway track circuit coding equipment, this paper proposed an automatic generation method of railway coding wiring tables based on image recognition to improve the accuracy and work efficiency of generating wiring tables from coding equipment construction drawings. The paper combined computer vision technology with coding principles, used OpenCV tools to automatically parse equipment parameters and wiring correlation information in engineering drawings, and generated standardized Excel wiring tables for on-site actual wiring operations. Combined with the equipment composition characteristics of two-wire pre-superimposed coding, the paper designed and developed an automatic coding wiring table generation software based on the Visual Studio and Qt cross-platform architecture, and carried out verification experiments to test the recognition and matching accuracy of the software for coding circuit diagrams in different sections. Experimental results show that this method can efficiently generate railway coding wiring tables, significantly improve the accuracy and efficiency of construction and maintenance work, and provide a reliable automatic tool for the automatic generation of coding wiring tables in railway signal systems.