• Tara V K
• Yashashree R
• Shoba H N
• Sonam Vishwakarma

Creating an automated categorization system for medicinal plants is a time-consuming and challenging task. India is a nation with a varied variety of plant species, each with its unique set of therapeutic qualities. Because it is hard for humans to recall the names of all plant species and their applications, previous knowledge is essential for manual identification and categorization. The preservation of these therapeutic plants is crucial as it will help a broad variety of sectors, including medicine, botanic research, and plant taxonomy studies, among others. Existing technologies cannot imitate the range of therapeutic plant species present in India. The suggested technique facilitates in the classification of medicinal plants by exploiting textural aspects that are crucial in leaf recognition and identification. The three key phases of the proposed technique are picture enhancement, feature extraction, and classification. The photographs of the leaves are shot using cellphones and then processed using digital image processing algorithms to extract the features that may be compared between them. Finally, the CNN classifier is employed to develop an automated classifier.

Leaf Identification, Feature extraction, Image processing, CNN

"IDENTIFICATION OF MEDICINAL PLANTS WITH IMAGE PROCESSING USING MACHINE LEARNING", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.11, Issue 5, page no.407-412, May-2024, Available :http://www.jetir.org/papers/JETIRGG06065.pdf

"IDENTIFICATION OF MEDICINAL PLANTS WITH IMAGE PROCESSING USING MACHINE LEARNING", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.11, Issue 5, page no. pp407-412, May-2024, Available at : http://www.jetir.org/papers/JETIRGG06065.pdf