Identification of Different Medicinal Plants Through Image Processing

Identification of medicinal plants and raw materials is crucial for various applications including pharmaceuticals, herbal remedies, and conservation efforts. Conventional methods of recognition often rely on expert intelligence and instructions investigation which container be time-timewasting and lying to oversights. In this study, we propose a novel approach for automating the identification process using image processing and machine learning algorithms. Specifically, we leverage advanced techniques such as deep learning with ResNet-50, and Random Forest algorithms to accurately classify images of medicinal plants and raw materials. Additionally, we integrate a leaf disease detection system using Keras to further enhance the functionality of the platform. The developed system includes a user-friendly website with features such as a blog page for sharing information and seamless integration of the image processing algorithms using the Django framework. Investigational results display the efficacy of the anticipated method in precisely discovering medicinal plants and raw materials, paving the way for applications in various domains.