As modern society increasingly rejects traditional knowledge and relies more heavily on synthetic medications, the need for the accurate identification of medicinal plants has become more critical than ever. This shift away from natural remedies poses several risks, including the potential misuse of medicinal plants owing to incorrect identification. Our project sought to address this issue by utilizing image-processing techniques, specifically grayscale conversion and Canny edge detection, to develop a more reliable approach for recognizing medicinal plants. By mitigating the risks of misidentification, this approach not only helps preserve and promote the use of natural remedies but also ensures that future generations can continue to benefit from their healing properties.