Basketball teaching is an important part of school physical education (PE) curriculum. It is welcomed and loved by many students. When choosing sports, they are always popular with students. However, with the development of education and the change of the situation, basketball teaching has become more and more complex and inefficient. In the era of rapid development of the Internet, teachers should fully understand and apply the network. This text first analyzed the theoretical basis of the goal of basketball education, and explained the importance of implementing quality education in teaching and paying attention to the cultivation of students’ innovation ability. This text proposed that the orientation of basketball education goals should be based on PE. Then this text analyzed the current basketball curriculum teaching and basketball track image information. It focused on the analysis of three problems: the limitation of teaching content, the lack of optimization and expansion, the limitation of basketball teaching, the lack of extension in the class, and the lack of basketball movement track image information. It pointed out that these problems seriously affect the development of current basketball teaching, and these problems should be solved in time. Then this text proposed to use image video sequence analysis algorithm to strengthen basketball flight path analysis, and proposed the positive value and basic principles of image recognition technology (IRT) in college basketball teaching. This text proposed to improve the application of IRT in basketball flight trajectory, create diversified curriculum content based on IRT and innovate basketball teaching methods based on IRT. Finally, this text combined image and video sequence analysis algorithm with experimental investigation and analysis. According to the experiment and investigation, the image video sequence analysis algorithm was introduced into the construction of basketball trajectory image information. A new image information system of basketball movement track was designed, which can improve the detection efficiency of basketball flight path analysis by 25.8%.
