The railway signal system is an important technical means to ensure the safe and efficient operation of railway transportation. As a key equipment of the railway signal system, the completeness testing of the system itself is essential for the computer interlocking system. The interlocking human-machine interface is an important component of the interlocking system. Through the operation of the operators, control commands can be sent to the signal equipment, and on-site equipment status information can be received and displayed. Testing the interlocking human-machine interface according to standard specifications is an important technical means to ensure the normal operation of the interlocking system and ensure the safety of railway operations. At present, the testing of interlocking human-machine interfaces mostly relies on manual labor, which has problems such as low testing efficiency and untraceable testing processes. This article proposes a template matching scheme suitable for real-time graphical interface detection based on the normalized squared difference algorithm; analyze the local features of the interlocking human-machine interface image and propose a non-invasive and distortion free image pixel feature recognition method; modeling and abstracting manual operation steps into computer recognizable language; propose 13 custom keywords to simulate interlocking human-machine interface operations; automatically capturing and analyzing image, text, and speech information, accurately calculating the RGB primary color model values of the image, determining the compliance of test results with specifications, and improving the accuracy and consistency of detection results. After verification and comparison, the proposed interlocking human-machine interface detection method has achieved full process automation testing, visualized all operation processes, and traceable test results and intermediate links, greatly improving testing efficiency and the credibility of test results.