Research on Intelligent Recognition and Verification System of Football Offside Penalty Based on Artificial Intelligence

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Gang Liu, Leqiang Zhang, Xiaodong Feng

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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