Plant Leaf Disease Detection using SVM-IWD Approach

Authors(1) :-Asha Rathee

Human is a social animal with their great dependence on plants in the direct or indirect manner. Plant provides us food, fruit, living resources like oxygen etc. Crops are also the part of plant category. So, there should be proper care of plants. There are various reasons in which plants can be affected or crops can be destroyed. In this research work, SVD-IWD approach is used for the plant disease detection. Plant diseases are analyzed from their leaves. Here, SVD (Support Vector Machine) is used to classify plant diseases and IWD (Intelligent Water Droplet algorithm) is used to optimize the evaluated results. For the experimentation, dataset of plant leaf affected from bacterial disease ‘Bacterial Blight’ and fungal diseases ‘Alternaria Alternata’, ‘Fungal Leaf Spot’ and ‘Fungus Anthracnose’ are considered. Overall results are evaluated in terms of accuracy in comparison with individual SVM approach

Authors and Affiliations

Asha Rathee
Department of Computer Science & Application, Maharshi Dayanand University, Rohtak, India

Plant Disease Detection, Support Vector Machine, Intelligent Water Droplets algorithm, Swarm Intelligence,

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Publication Details

Published in : Volume 2 | Issue 4 | July-August 2017
Date of Publication : 2017-08-30
License:  This work is licensed under a Creative Commons Attribution 4.0 International License.
Page(s) : 944-949
Manuscript Number : CSEIT11833753
Publisher : Technoscience Academy

ISSN : 2456-3307

Cite This Article :

Asha Rathee, "Plant Leaf Disease Detection using SVM-IWD Approach", International Journal of Scientific Research in Computer Science, Engineering and Information Technology (IJSRCSEIT), ISSN : 2456-3307, Volume 2, Issue 4, pp.944-949, July-August-2017.
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