This paper focuses on the research of intelligent digital teaching resources generation method based on image processing technology, aiming at solving the problems of low efficiency, slow updating and insufficient personalization in the traditional teaching resources generation process. By analyzing the core technologies of image processing, including image recognition, image segmentation, image enhancement and target detection, an intelligent resource generation model for educational scenarios is constructed, and the corresponding automated processing flow is designed to realize the intelligent generation of the whole process from the original image acquisition to the output of structured teaching content. Experiments and case studies show that the method has significant advantages in improving the efficiency of resource generation, enriching the expression of teaching content and enhancing the interactivity of learning, providing technical support for the development of education informatization, personalization and popularization. The study shows that the introduction of image processing technology into teaching resource generation not only has practical application value, but also provides new ideas and directions for the development of intelligent education.
Juan Du (Sun,) studied this question.