Abstract: Cricket umpiring, particularly for Leg Before Wicket (LBW) decisions, plays a crucial role in determining match outcomes. Traditional umpiring methods rely on human judgment, which can sometimes lead to errors due to limited reaction time and viewing angles.
To improve accuracy and minimize human error, this paper presents an AI-based cricket umpire system that utilizes computer vision and polynomial curve fitting for LBW decision-making.
The system processes video frames, detects the cricket ball using HSV color segmentation, tracks its movement, and predicts its impact using trajectory analysis.
Keywords: Cricket, AI Umpire, LBW Decision, Computer Vision, OpenCV, Trajectory Prediction, SciPy, NumPy.
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DOI:
10.17148/IJARCCE.2025.14258
