Affiliations:
Institute of Physical Education, Jiaozuo Normal College, Jiaozuo, China
Correspondence:
[*]
Corresponding author. Jingbo Wang, Institute of Physical Education, Jiaozuo Normal College, 454000, Jiaozuo, China. E-mail: [email protected].
Abstract: Aiming at the problems of large error and poor robustness of traditional image classification methods, a three-dimensional martial arts image classification algorithm based on symmetry theory is proposed. According to the preprocessed 3D martial arts image, the classification algorithm based on symmetric neural network is used to realize the classification of 3D martial arts image. The experimental results show that the minimum error rate of this algorithm is 6.1%, which is far lower than the traditional algorithm, it is shows that the improved algorithm has higher definition, better robustness, and the test results of different topological nodes on the test solution show that the average error rate of the algorithm is lower. Compared with the same type of algorithm, the application value of the proposed algorithm is significant.
Keywords: Denoising, sharpening, SDBN network, mean filtering, gray uniformity
