Digital image processing is an integral part of the computer vision field. However, traditional digital image processing teaching methods mainly focus on theoretical knowledge, lacking practical teaching content. To address this issue, this article proposes a project-based learning (PBL) model that consists of four key stages: project proposal, implementation, summary, and evaluation. Instructors design one or more digital image processing projects in the project proposal stage with specific objectives, backgrounds, content, and deliverables. During the implementation stage, students work on the projects under close guidance, applying various teaching methods such as independent learning, teamwork, and academic exchange. The summary stage involves students reflecting on and evaluating their project outcomes, challenges, and potential improvements. Finally, the evaluation stage utilizes a comprehensive, operable, impartial, and traceable system to assess project completion quality and student performance. Through case studies, this project-based learning model demonstrates how it can help students better understand the theoretical knowledge of digital image processing, apply it to practical projects, and improve their ability to apply theoretical concepts to practical operations. Ultimately, this improves teaching quality and facilitates the achievement of teaching goals. © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2025.
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