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All Journal Jurnal Sistem Informasi Triguna Dharma (JURSI TGD) Journal of Artificial Intelligence and Digital Business Journal of Computer Science and Research
Lubis, Syaiful Rahman
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Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Electrical & Electronics Engineering Engineering Library & Information Science

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Journal : Journal of Computer Science and Research

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A Study on Implementation and Performance Analysis of Basic and Advanced Image Processing Techniques Using Python and OpenCV Lubis, Syaiful Rahman; Iqbal, Muhammad
Journal of Computer Science and Research (JoCoSiR) Vol. 2 No. 2 (2024): April: Computer Science
Publisher : Asosiasi Perguruan Tinggi Informatika dan Ilmu Komputer (APTIKOM) Provinsi Sumatera Utara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.65126/jocosir.v2i2.60

Abstract

Abstract— Digital image processing plays a crucial role in artificial intelligence and computer vision, with widespread applications in healthcare, agriculture, security, industry, and transportation. This research focuses on implementing both basic and advanced image processing methods using Python and the OpenCV library within a desktop application. The main problem addressed is the lack of an integrated, structured approach that bridges basic and advanced techniques, limiting users' comprehensive understanding of image processing workflows. The objective is to design a complete system that allows step-by-step processing, starting from grayscale conversion, binarization, arithmetic and logical operations, to convolution and morphological transformations such as Sobel edge detection and erosion. The proposed application utilizes Tkinter for the user interface, enabling users to upload images, apply various processing techniques, and analyze results interactively. The system also includes histogram visualization and equalization to enhance contrast. Findings show that the implemented methods effectively transform images in accordance with theoretical expectations, such as edge enhancement and shape simplification. The integration of these methods into a single, user-friendly platform supports both educational and applied uses. The contribution of this research lies in its practical demonstration of digital image processing techniques, providing a comprehensive and accessible reference for developers, researchers, and students. Despite its achievements, the system lacks advanced segmentation and real-time capabilities, which are suggested for future development through integration of adaptive methods and machine learning techniques.
Co-Authors Muhammad Iqbal Muhammad Syahputra Novelan Prayogi, Dhimas Rizko, M. Azhari Sri Murniyanti Suteja, Ade Guna Tengku Riza Zarzani N