Detection and Classification of Plant Diseases Using Image Processing and Multiclass Support Vector Machine

© 2020 by IJCTT Journal
Volume-68 Issue-4
Year of Publication : 2020
Authors : Murtaza Ali Khan
DOI :  10.14445/22312803/IJCTT-V68I4P102

How to Cite?

Murtaza Ali Khan, "Detection and Classification of Plant Diseases Using Image Processing and Multiclass Support Vector Machine," International Journal of Computer Trends and Technology, vol. 68, no. 4, pp. 5-11, 2020. Crossref,

Identification of plant disease is very important to prevent the loss and keep the harvest healthy. Determination of plant disease via visual monitoring is difficult and time consuming. In this paper, we described a method of detection and classification of plant disease using image processing and machine learning techniques. We used standard images of leaves of several types of plants to test our method. Initially, our method segments the input image to isolate disease parts of the leaf. Then we obtain various features from the diseased affected segmented image. Finally, we classify leaves into healthy and disease types based on its features using Multiclass Support Vector Machine (SVM) classifier. Experimental results indicate that our method yields very high accuracy rate for detection and classification of plant diseases.

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Detection, Classification, Plant Diseases, Image Processing, and Multiclass Support Vector Machine