Abstract
Oil painting education not only helps to improve students’ drawing skills and quality but also fosters creative thinking in the field of art. In order to keep up with the development of art diversity, it is essential to establish the concept of art diversity education and reform university oil painting education to meet the needs of modern society. This study aims to explore the potential value of image optical processing technology based on computer vision in the application of oil painting teaching image simulation. In order to improve students’ ability of oil painting simulation, this paper presents an image optical processing technology based on computer vision. The study collected a large number of oil painting images and teaching samples. Then, through image processing algorithm, we extract and analyze the optical features in the oil painting works, and then design an optical simulation method to apply these features to the students’ simulation works. By comparing the traditional methods and the techniques proposed in this paper, the image optical processing technology based on computer vision has potential practical value in the application of oil painting teaching image simulation, which can help students better understand and simulate the optical effects of traditional oil paintings.
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Funding
This paper was supported by (1) Research on the Forms and Development of Regional Art in the Guangxi Zhuang Autonomous Region(Project No:20FZX007); (2) 2022 Fifth Round of Guangxi Normal University Ideological and Political Model Curriculum Development Key Project “The Fundamentals of Oil Painting” (Project No.: 2022kcsz13).
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CF has done the first version, LZ has done the simulations. All authors have contributed to the paper’s analysis, discussion, writing, and revision.
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Fujun, C., Zhenliang, L. Application of image optical processing technology based on computer vision in image simulation of oil painting teaching. Opt Quant Electron 56, 511 (2024). https://doi.org/10.1007/s11082-023-06138-0
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DOI: https://doi.org/10.1007/s11082-023-06138-0