Automatic detection technology for sports players based on image recognition technology: the significance of big data technology in China's sports field

In this research, players are investigated physically for the actual analysis to improve the recognition of motion effects based on image recognition technology. In this paper, the incorporation of the status of image recognition science has been tested on the athletes through image processing using artificial intelligence technology (IPAIT). Furthermore, the segmentation of gradient procedure has been validated using image segmentation techniques with big data assistance. In AIT, enhancing the traditional method of a grayscale image and obtaining the reconstructed image segmentation algorithm has been designed and developed. Furthermore, big data-assisted Gaussian background and IPAIT modeling are used to identify the target for the feature extraction of the human body and use morphological operators to deal with noise. The simulation findings demonstrate that the proposed IPAIT model enhances the recognition ratio of 98.8%, a performance ratio of 97.7%, and increases the accuracy ratio by 95.9% compared to other existing models.