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In this manuscript, we present score recognition techniques for blowgun game based on computer vision. First, the algorithm detects the position of the target, and calibrates the camera's parameters. Then the score is calculated with the detection of the dart tip on the target for real-time applications. To improve the robustness, the initial calibration is proposed to record N points as references at the edges of circles, to correct the camera position and angle. This approach can overcome the problems of lighting changes and the camera viewing angle deviation. The fast segmentation and orientation decision is proposed to find the blowgun tip accurately. The two cameras are presented to solve the overlapping problem of multiple darts to improve the detection accuracy. Based on calibration parameters, the distance weighting method is proposed to calculate the score precisely. Experiments result that the accuracy can achieve about 97% to recognize the score, and the processing speed can meet the real-time requirement with software implementation.

Intelligent Blowgun Game Scoring Recognition System Based on Computer Vision