Combination of Machine Learning Approach for Classifying Important Medicinal Crops

In this study, we use image processing & machine learning approaches to the problem of medicinal plant categorization based on leaf attributes. Medicinal herbs have critical roles in many different medical traditions, and this research emphasises how important it is to accurately identify them. The suggested method begins with image preprocessing to improve the quality of the leaf pictures, followed by image segmentation to extract the leaf features. After the leaves have been subdivided, feature extraction methods are used to record additional information about them, such as their colour, texture, and shape. Using the collected characteristics, the leaf samples are categorised into distinct groups using machine learning methods like Multi-Layer Perceptron (MLP) & Decision Tree. The automated leaf categorization system has the potential to improve medicinal plant industries' quality control, authentication, & inventory management. Correctly identifying medicinal plants is an important step towards guaranteeing the efficacy and safety of herbal remedies. Herbal medicine practitioners and manufacturers alike may reap the benefits of improved efficiency and accuracy in medicinal plant identification thanks to the use of image processing & machine learning methods.