A Comprehensive Review of Plant Recognition Approaches: Techniques, Challenges, and Future Direction

Abstract

Ayurveda, the ancient Indian system of medicine, relies heavily on the use of medicinal plants, which not only serve as the foundation of this holistic practice, but also provide a lucrative source of income. India is renowned for providing an ideal habitat for a diverse array of medicinal plants, with different parts of these plants being used as key components in the production of natural remedies. Interestingly, many of these medicinal plants can be found growing in our very own backyards or along the sidewalks. It is next to impossible for untrained person to identify and distinguish between various medicinal plants. Identifying plant species through manual processes is a challenging and time-consuming task, often made more difficult by a lack of expertise in the field. This is particularly true when it comes to correctly identifying and classifying medicinal plants, which can be a complex and confusing process. To address these challenges, this study seeks to leverage the power of machine learning to automatically detect medicinal plants, streamlining the identification process and reducing the need for manual labor. By automating this critical task, the study aims to improve efficiency and accuracy, while also making it more accessible to individuals with varying levels of expertise. This comparative study will also explore the accuracy of single attribute plant identification systems and examine the potential for incorporating multiple attributes in future systems to enhance their overall effectiveness.