The existing target reporting systems are mainly designed for single-ring targets and lack solutions for recognizing the number of rings in three-ring targets. This paper proposes an automatic target reporting system based on multi-camera vision and convergence algorithm for the recurve triple target, aiming to achieve efficient and accurate recognition of multi-ring targets. The system uses four cameras to capture images of the target from different angles and detects the position of the arrow landing point and calculates the number of rings through image processing and feature extraction. The system demonstrates significant robustness and accuracy in handling complex scenarios such as occlusion and angle errors. It can utilize redundant camera data to handle occlusion problems, reduce perspective distortion errors by averaging data from multiple perspectives, and has an intelligent fallback mechanism that can automatically select the optimal data combination based on data availability. Additionally, the system can improve positioning accuracy by determining the same arrow area in different cameras and dynamically adjust the weight of each camera's data in the final result based on the reliability and data quality of the cameras. The recognition accuracy of this system reaches 94.5%, which is 26.5% higher than that of the traditional binocular camera system.