Automatic Generation Method of Basketball Continuous Pitching Action Based on Multi-Objective Machine Vision

Abstract

In order to improve the effectiveness of basketball continuous pitching motion guidance, the image characteristics of basketball continuous pitching motion are analyzed with image processing method, and an automatic generation method of basketball continuous pitching motion based on multi-objective machine vision is proposed. The method comprises the following steps of: establishing a shape feature point feature matching model of a basketball continuous pitching motion fuzzy image; extracting posture key action points of the basketball continuous pitching motion fuzzy image by combining a spectral feature detection method; carrying out adaptive enhancement processing on the basketball continuous pitching motion fuzzy image by adopting a shape feature segmentation method; and obtaining sub-band pixel feature points of the basketball continuous pitching motion fuzzy image by combining a point tracking matching method and a feature extraction method. The fuzzy image of basketball continuous pitching motion is enhanced to improve the expression ability of posture information of fuzzy noise points in the image. The significant contrast enhancement processing of the fuzzy image of basketball continuous pitching motion is carried out through the point tracking recognition method, and the multi-objective machine vision features of the fuzzy image of basketball continuous pitching motion are extracted to realize automatic generation and accurate recognition of the fuzzy image of basketball continuous pitching motion. The simulation results show that the output peak signal-to-noise ratio automatically generated by using this method for basketball continuous pitching motion is higher, and the image recognition ability is better. Therefore, it is necessary to improve the performance of the system.