Abstract: In this paper, we present a real-time scoring algorithm for steel dartboards, by using five (configurable) low-cost cameras that are positioned parallel to the baseline (surface) of the dartboard. In order to achieve that, firstly the cameras are placed at suggested places. Then, their central focus is configured to look at the center of the dartboard. Subsequently, the dartboard is calibrated and thresholds are adjusted for each camera respectively. After this step, the software runs and processes in real-time, detecting the darts with high precision as they are thrown. The algorithm is a daemon process, requiring high processing power. We detect parts that require long processing times by profiling the algorithm. Using techniques of parallel-programming, important parts of the algorithm are adjusted to run in parallel, in order to achieve a real-time effect. In our experiments, our algorithm achieved a detection accuracy rate of 99.63%, by using five low-cost cameras having an 85 degree horizontal field of view (HFOV). Simultaneously, each throw is detected in less than 600 ms, giving the real-time effect to players. This algorithm is tested with a variety of professional steel dartboards, and dart arrows of different materials (tungsten, steel etc.). The obtained outcomes indicate the robustness of the proposed algorithm, producing promising results.
Keywords: Steel tip dartboard, automatic scoring, hit detection, computer vision, image processing, real-time processing
DOI: 10.3233/ICG-230214
Journal: ICGA Journal, vol. 44, no. 3, pp. 72-90, 2022
