Research on Intelligent Recognition and Verification System of Football Offside Penalty Based on Artificial Intelligence
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Abstract
An automatic recognition method for ball trajectory and penalty is extensively studied, leveraging computer vision
technology. The core hardware components of this system are designed to effectively filter out noise and extract crucial information
from the moving track. This enables the system to accurately identify the speed and position of the ball in real-time. To enhance the
precision of image segmentation, a novel approach is introduced that utilizes the threshold vector in high-resolution color spaces. This
method determines the color of each pixel through bitwise "and" operations between pixel points and subsets. Additionally, a moving
window image filtering algorithm is proposed, incorporating trajectory prediction theory. Experimental results demonstrate that this
approach significantly reduces recognition errors, resulting in a notably higher accuracy level, making it a promising solution for
enhancing the performance of soccer robot systems.
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