In the context of the digital age, various digital technologies have appeared, such as wireless networks and multimedia technologies have been used maturely in teaching. The traditional method is rigid, just teaching blindly, while digital teaching can break through the time and space constraints, teachers & students can interact in real time through wireless networks and multimedia devices, creating a positive learning atmosphere. In recent years, an increasing number of teachers have applied digital media (abbreviated as DM here) technology to teaching activities. On the one hand, DM itself has the advantages of convenient operation and comprehensive functions. On the other hand, it can be used to build a teaching system that conforms to the features of modern education. In the digital media teaching (abbreviated as DMT for short) system, digital video is a regularly used teaching method. Whether teachers or students, they can use computers, tablets, intelligent drawing boards and other multimedia devices to find teaching resources and learn teaching content. With the increase of the number and types of videos, the conventional DMT system has exposed shortcomings such as slow video processing speed, video recommendation errors, etc., which ultimately led to a continuous decline in teaching effectiveness. Cloud computing is an advanced network technology, which can process various data accurately and quickly. At present, this technology is quite mature. Under this background, this text studies the video image analysis in DMT with cloud computing. By analyzing the components of cloud computing system (CCS), this text summarizes its application in DMT, and then gives the implementation process of video image analysis in DMT based on image analysis, and finally adds a video image analysis algorithm based on deep learning (DL). The experimental results show that the teaching efficiency is improved by 9.72% after the implementation of the new image analysis application strategy, and the new video image analysis method also improves the processing efficiency of teaching videos.
