Identification of Different Medicinal Plants/ Raw Materials Through Image Processing Using Machine Learning Algorithms

Identifying medicinal plants and their raw materials precisely and efficiently is essential for industries such as pharmaceutical, nutraceutical, cosmetics and traditional medicine products. Traditionally, this process depends on the expert knowledge of the appearance, structure and classification of a plant. However, these methods are often slow, intensive in labor and can be prone to errors. In many remote areas or resources little resources, where a large number of valuable medicinal plants grow, qualified botanists cannot be available. This can lead to erroneous identification or adulteration of plant materials, which not only reduces the effectiveness of products, but can also raise serious health risks and cause financial losses. To address these challenges, this research focuses on developing a faster, more reliable and profitable solution through the use of image processing and automatic learning to automate the identification of medicinal plants and their raw forms.