Real-Time Arrow Detection and Scoring on Archery Targets Using YOLOv8 with Euclidean Distance-Based Zone Estimation
DOI:
https://doi.org/10.30871/jaic.v9i6.11086Keywords:
computer vision, euclidean distance, archery, cnn, yolo v8Abstract
The current study aims to create an automated scoring system for archery target board using computer vision technologies. As archery has develop from a traditional practice to a competitive activity, the scoring procedures have become a crucial element. While the current manual scoring procedures are fallible and can be challenging for organizers. This study offers a solution to this issue by using YOLO v8 (You Only Look Once) architecture for real- time arrow recognition and scoring. The development process consists of dataset collecting, picture pre-processing, model training and implementation using 2 photos of the target boards with arrows. The computer processes the scores by calculating the distance from the center of the arrow to the selected scoring zones using Euclidean distance. System testing established a baseline accuracy of 67%. While users noted the system's processing efficiency (speed), this accuracy level highlights significant room for improvement. The results demonstrate the potential for applying computer vision to automate the archery scoring system, while simultaneously emphasizing the critical need for advanced model performance enhancements. This study serves as a preliminary step in exploring automated sport technology, expected to contribute to future refinements of the archery scoring system.
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