Siahaan, Andysah Putera Utama and Yasri, Afif and Marbun, Ramlan and Alfikri, Muhammad Daffa and Putra, Khairil (2025) Design of GUI-based digital image processing applications in python using OpenCV and Tkinter. World Journal of Advanced Engineering Technology and Sciences, 16 (1). 049-055. ISSN 2582-8266
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Abstract
Digital image processing is an important field in computer science that enables the manipulation and analysis of visual data for various practical applications. This study presents the development of an interactive desktop application for digital image processing using Python, OpenCV, and Tkinter. The purpose of this research is to provide a user-friendly graphical interface that simplifies the use of common image processing techniques, especially for non-technical users. The application includes features such as image upload, grayscale conversion, binary thresholding, brightness adjustment, logical AND operation, image sharpening, dilation, RGB histogram visualization, image reset, and result saving. The prototyping development model was adopted to ensure iterative refinement based on functionality and usability. The core methods were implemented using the OpenCV library for image processing operations, while Tkinter was used to design the GUI components. Experimental results demonstrated that the application successfully processed digital images and displayed both original and processed outputs side by side. Each feature functioned as expected and contributed to enhancing image quality or extracting relevant information. The integration of a visual interface with underlying technical operations enables users to interact more intuitively with image processing tasks. This application offers a practical tool for education, experimentation, and further development in the field of digital image processing.
Item Type: | Article |
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Official URL: | https://doi.org/10.30574/wjaets.2025.16.1.1196 |
Uncontrolled Keywords: | Image Processing; OPENCV; Application Gui; Python |
Depositing User: | Editor Engineering Section |
Date Deposited: | 22 Aug 2025 07:20 |
Related URLs: | |
URI: | https://eprint.scholarsrepository.com/id/eprint/5198 |