If there are defects in the vertical tail composite parts of an aircraft, it will affect the balance of the aircraft during navigation and pose a threat to the safety of aircraft navigation. To effectively ensure the safe operation of the aircraft, a machine vision based defect detection method for vertical tail composite parts of an aircraft is proposed. Establish a part defect image acquisition system based on machine vision principles, and collect defect images of composite material parts at the vertical tail of aircraft. Extract the defect image ROI area from the collected image, capture external features such as width, thickness, and dispersion in the extracted area, and compare them with the standard parameters generated during the part configuration process to achieve defect detection of the part. The experimental results show that using this method for defect detection of aircraft vertical tail composite parts has good detection effect and high accuracy.