Performance Analysis and Error Detection in 10m Air Pistol Shooting

This paper presents an automated system for analyzing ten-shot pistol shooting targets using computer vision and statistical analysis. The proposed method processes a scanned or photographed target image to detect pellet holes, convert shot positions into real-world target coordinates, and evaluate shot grouping characteristics. A rule-based knowledge system is used to classify shooting errors into mechanical, physical, and mental categories and provide corrective recommendations. The system ensures objective, repeatable, and competition standard analysis, making it suitable for learning from the shooter’s errors and mistakes.