A Neoteric Procedure for Spotting and Segregation of Ailments in Mediciative Plants using Image Processing Techniques

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Published Nov 18, 2022
https://doi.org/10.47164/ijngc.v13i4.965
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Volume 13, Issue 4, November 2022

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Rakesh Kumar Yadav
Department of Computer Science & Engineering, MSOET, Maharishi University of information Technology, Lucknow, UP, India
Ankit Kumar
Babu Banarasi Das Institute of Technology & Management, Lucknow
Santosh Kumar Shukla
Associate Professor, Department of Computer Science and Engineering, Babu Banarasi Das Engineering College, Lucknow
Eram Fatima
Babu Banarasi Das Institute of Technology & Management, Lucknow

Abstract

Nowadays, health of medicinal plant is sincerely observed for the manufacture of medicines. The features of medicinal plants take a very crucial role for the health. In this work, features of medicinal plants are analyzed for the recognition of infected and non-infected measures. Nowadays, many countries have moved to Ayurveda. Medicinal plants are harvested similarly to food crops harvested in the agricultural field. Diseases in plants reduce the quality and quantity of the product. Also, the medicines would not be helpful if prepared using a diseased plant. Thus, monitoring health is a must requirement. Manual inspection is a tiring task with a massive loss of budget and time, and the loss increases with the agricultural field size. Thus, image processing techniques have proven to be beneficial for detecting, identifying, and classifying diseases in medicinal plants as it reduces the tiresome inspection of the field and saves time and money. With image processing techniques, diseases can be detected as early as when they start appearing on the surface of the plants, thus helping in taking appropriate preventive measures to stop the growth of the disease, even stopping it from occurring in the future. Detection, identification, and classification of diseases using image processing techniques comprises steps like image acquisition, preprocessing, image segmentation, feature extraction, and classification. Here, different techniques are described for the detection purpose. Also, a new technique is proposed for identifying and classifying diseases in medicinal plants. The overall accuracy for the feature recognition is 91 percent after all the iterations and the model is found to be robust.

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This work is licensed under a Creative Commons Attribution 4.0 International License.

How to Cite
Rakesh Kumar Yadav, Ankit Kumar, Santosh Kumar Shukla, & Eram Fatima. (2022). A Neoteric Procedure for Spotting and Segregation of Ailments in Mediciative Plants using Image Processing Techniques . International Journal of Next-Generation Computing, 13(4). https://doi.org/10.47164/ijngc.v13i4.965
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