Pukhrambam, Banita and Rathna, R. (2021) A Smart Study on Medicinal Plants Identification and Classification using Image Processing Techniques. In: 2021 Third International Conference on Intelligent Communication Technologies and Virtual Mobile Networks (ICICV), Tirunelveli, India.
![[thumbnail of A Smart Study on Medicinal Plants Identification and Classification using Image Processing Techniques _ IEEE Conference Publication _ IEEE Xplore.html]](https://ir.vistas.ac.in/style/images/fileicons/archive.png)
A Smart Study on Medicinal Plants Identification and Classification using Image Processing Techniques _ IEEE Conference Publication _ IEEE Xplore.html
Download (269kB)
Abstract
Plants play an important role in human life for providing oxygen, food, housing, medicine, energy, housing, and environmental protection. Plants are rich in medicinal esteem and contain dynamic elements for medicinal use because of the global warming populace, lack of expert help for research, lack of government upholding research exercises, and familiarity with medicinal plants. Numerous utility plants are getting pulverized. Manual identification of plants requires significant investment and requires the identification of plants with the help of experts. To address this issue, individuals need to acquire a more prominent advantage in robotized identification and medicinal plant classification. The research region's image process field is dynamic in the automatic identification and classification of medicinal plants. Feature extraction and classification are the important developments in identifying medicinal plants that affect the overall accuracy of the system for scientific categorization. This research examines recent methods of image processing for the classification of medicinal plants.
Item Type: | Conference or Workshop Item (Paper) |
---|---|
Subjects: | Computer Science Engineering > Natural Language Processing |
Divisions: | Computer Science Engineering |
Depositing User: | Mr IR Admin |
Date Deposited: | 20 Sep 2024 09:49 |
Last Modified: | 20 Sep 2024 09:49 |
URI: | https://ir.vistas.ac.in/id/eprint/6721 |