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Deep Learning based Recognition of the Indian Medicinal Plant Species | IEEE Conference Publication | IEEE Xplore

Deep Learning based Recognition of the Indian Medicinal Plant Species


Abstract:

Since the dawn of time, medicinal plants, usually referred to as medicinal herbs, have been employed in traditional medicine. Numerous substances are produced by plants f...Show More

Abstract:

Since the dawn of time, medicinal plants, usually referred to as medicinal herbs, have been employed in traditional medicine. Numerous substances are produced by plants for purposes including defense against pests, diseases, fungus, and herbivorous animals. Antiquated Ayurvedic original copies, Egyptian papyrus, and Chinese books portray the utilization of spices. Medicinal plants and herbs have been used as medicines for over 4000 years. Plant parts such as flowers, leaves and roots are highly medicinal. However, it is a difficult process for agronomists and pharmaceutical companies to identify suitable medicinal plants, resulting in the loss of ancient knowledge of Ayurveda. This research work proposes an automated system to identify plants by using a CNN model. To identify rare new species, a thorough understanding of plants is required. Changes in leaf properties are useful for conducting comparative studies of plants. Therefore, this automated system will help to identify medicinal plants and helps agronomists identify the correct herbs.
Date of Conference: 21-23 September 2022
Date Added to IEEE Xplore: 29 December 2022
ISBN Information:
Conference Location: Coimbatore, India
References is not available for this document.

I. Introduction

In our daily lives, we often encounter many kinds of plants and trees. A few plants are easy to identify, but of the plants are difficult to identify, especially when they are of medicinal importance. There are around 8000 [1] species of medicinal plants found in India. Medicinal plants are most commonly found in the tropics, but botanical studies in these areas take a long time. Since the dawn of time, medicinal plants, usually referred to as medicinal herbs, have been employed in traditional medicine [2]. Plants produce a variety of chemicals to protect themselves from insects, fungi, diseases, and herbivorous mammals. Many highly effective species have not yet been discovered. Proper identification of these medicinal plants solves many diseases. The most difficult task is to identify many such plants. Some plants we see are unrecognizable except for their lifetime. Finding these plant species requires a great deal of knowledge and understanding [3]. Identifying these plants will not only help to cure many diseases, but also will help to restore the traditional knowledge of Ayurveda and ancient medicine. It will help the agronomists, ayurvedic medicine practices to identify the medicinal plants easily.

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1.
India is home to over 8,000 species of medicinal plants - and they're increasingly under threat - https://scroll.in/article1954167/india-is-home-to-over-8000-species-of-medicinal-plants-and-theyre-increasingly-mder-threat.
2.
Medicinal Plants. [cited 2022] ; Available from: https://en.wikipedia.org/wiki/Medicinal_plants.
3.
Amala Sabu, K Sreekumar and Rahul R Nair “Recognition ofayurvedic medicinal plants from leaves: a computer vision approach ” Proceedings of Fourth International Conference on Image Information Processing, Jaypee University of Information Technology, Shimla, 21–23 December, 2017, pp: 1–5.
4.
Ding Min Yue and Feng Qin “Plant leaf recognition based on naive Bayesian classification and linear discriminant analysis model ” Proceedings of Fourth International Conference on Communication and Information Systems, Wuhan, China, 19–21 December, 2019, pp. 191–196.
5.
D Venkatraman and N Mangay Arkarasi, “Computer Vision Based Feature Extraction of Leaves for Identification of Medicinal Values of Plants ”, Proceedings of IEEE International Conference on Computational Intelligence and Computing Research, Agni College of Technology, Chennai, Tamil Nadu, India, 15–16 December, 2016, pp. 1–5.
6.
B. Raja, M. Anand, V. Malathy and K. Sudhaman “Identification of Plants with their Medicinal Uses by Convolutional Neural Network ” Proceedings oflnternational Journal of Advanced Science and Technology, Vol. 29, Issue No 6s, 2020 pp. 1401–1408.
7.
Sue Han Lee, Chee Seng Chan, Wilkiny Paul and Remagninoz Paolo, “Deep-plant: plant identification with convolutional neural networks ”, proceedings of IEEE International Conference on Computational Intelligence and Computing Research, Quebec City, QC, Canada, 27–30 September, 2015, pp: 452–456.
8.
Nghia Duong Trung, Luyl Da Quach, Hoang Minh Ngyuen and Chi-Ngon Nguyen “A Combination of Transfer Learning and Deep Learning for Medicinal Plant Classification ” Proceedings of International Conference on Intelligent Information Technology, A Nang, Vietnam, Feburary, 2019, pp: 93–90.
9.
Boran Sekeroglu and Inan Yucel, “Leaves recognition system using a neural network ”, Proceedings of 12th International Conference on Application of Fuzzy Systems and Soft Computing, ICAFS, Vienna, Austria, 29–30 August, 2016, pp: 578–582.
10.
Elhariri Esraa, Nashwa EI-Bendary and Aboul Ella Hassanien, “Plant Classification System based on Leaf Features ”, Proceedings of IEEE International Conference on Computational Intelligence and Computing Research, Cairo, Egypt, 22–23 December, 2014, pp: 71–76.
11.
A Gopal, S Prudhveeswar Reddy and V Gayatri, “Classification of Selected Medicinal Plants Leaf Using Image Processing ” proceedings of IEEE International Conference on Machine Vision and Image Processing (MVIP), Coimbatore, India, 14–15 December, 2012, pp: 5–8.
12.
Basavraj S Anami, Suvarna S Nandyal and A Govardhan “A Combined Color, Texture and Edge Features Based Approach for Identification and Classification of Indian Medicinal Plants ”, proceedings of International Journal of Computer Applications, Volume 6, Issue No. 12, September 2010, pp: 45–51.
13.
Samreen Naeem, Aqib Ali, Christophe Chesneau, Muhammad H Tahir, Farrukh Jamal, Rehan Ahmad Khan Sherwani and Mahmood Ul Hassan “The Classification of Medicinal Plant Leaves Based on Multispectral and Texture Feature Using Machine Learning Approach ” proceedings of Agronomy, 11.263.1 0.3390, 2021.
14.
Shashank M Kadiwal, Venkatesh Hegde, Shrivathsa NV, Gowrishankar S, Srinivasa A. H, Veena A, “A Survey of Different Identification and Classification Methods for Medicinal Plants ” in the proceedings of 4th International Conference on Inventive Computation and Information Technologies, Coimbatore, India, 25–26 August, 2022, in press.
15.
Manoharan, Samuel “Image Detection, Classification and Recognition of Leak Detection in Automobiles ” Proceeding of Journal of Innovative Image Processing, Vol 01, Issue No 2, 2019, pp: 61–70.
16.
Dhaya, R. “Flawless Identification of Fusarium Oxysporum in Tomato Plant Leaves by Machine Learning Algorithm ” Proceedings of Journal of Innovative Image Processing, vol 02, Issue No 4, 2020, pp: 194–201.
17.
Segmented Medicinal Plants Dataset can be accessed from - https://www.kaggle.com/datasetslriteshranjansaroj/segmented-medicinal-leaf-images.
18.
To create diagrammatic models to represent certain workflows refer this link https://app.diagrams.net/.
19.
To convert a tensorflow lite model to tensorflow lite model - https://www.tensorflow.org/apidocs/pythonitf/liteITFLiteConverter.
20.
To build a convolutional neural network architecture from scratch - https://www.tensorflow.org/tutorials/images/cnn.

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References

References is not available for this document.