<![CDATA[ Digital image processing is an important part of computer science that is widely used in various fields, such as video, face, and automated systems. However, as a result of the presence of three colour channels (RGB), colour image processing presents a number of significant problems, including high memory usage and computational complexity. In contrast, many feature algorithms rely on image intensity. Conversion to grayscale can speed up the process and save memory as it simplifies the data by reducing three channels to one. Therefore, the purpose of this research is to implement the RGB to grayscale conversion process using the Python programming language and the OpenCV library. The method used includes collecting RGB data and then converting it to grayscale using OpenCV's built-in functions. The results show that the process runs well, simplifies the data structure, and produces a grayscale image that contains important information making it suitable for the final stage of image processing. Keywords: RGB, Grayscale, Image Processing, Python, OpenCV]]>
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