Automatic Recognition of Medicinal Plants: Based on Multispectral and Texture Features using Hidden Deep Learning Model
Murad Kabir Md. Rakib1, Himanish Debnath Himu2, Md. Omar Faruq Fahim3, Zahura Zaman4, MD. Jalal Uddin Rumi Palak5
1Murad Kabir Md. Rakib, Department of Computer Science, Daffodil International University, Dhaka, Bangladesh.
2Himanish Debnath Himu, Department of Computer Science, Daffodil International University, Bangladesh.
3Md. Omar Faruq Fahim, Department of Computer Science, Daffodil International University, Dhaka, Bangladesh.
4Ms. Zahura Zaman, Lecturer, Department of Computer Science and Engineering, Faculty of Science and Information Technology, Daffodil International University, Dhaka, Bangladesh.
5MD. Jalal Uddin Rumi Palak, Department of Computer Science and Engineering from Daffodil International University. Dhaka, Bangladesh.
Manuscript received on 04 February 2023 | Revised Manuscript received on 09 February 2023 | Manuscript Accepted on 15 February 2023 | Manuscript published on 28 February 2023 | PP: 1-7 | Volume-3 Issue-1, February 2023 | Retrieval Number:100.1/ijcgm.D40890412423 | DOI:10.54105/ijcgm.D4089.023123
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© The Authors. Published by Lattice Science Publication (LSP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Identification of medicinal plants automatically in the environments is necessary to know about their existence around us. Recently, there are many techniques followed to recognize plants automatically such as through leaves and flowers with their shape and texture. Leaf-based plant species identification systems are widely used nowadays. This proposed research work uses a deep learning approach using Convolutional Neural Networks (CNN) to recognize medicinal plants through leaves with high accuracy. For this research, leaf images are collected from nature and used as the experimental dataset. The authors have collected leaf items from 5 different medicinal plants. After the collection of images and have to pre-process them which plays an important role in the classification steps. Deep learning model and algorithm are used for classification purposes among them, VGG16 worked pretty well and got an accuracy level of 95.48%. In real life, this paper can well affect the medical sector and learn more about medicinal plants.
Keywords: Deep Learning, Transfer Learning, Convolutional Neural Networks, VGG19.
Scope of the Article: Deep Learning