Plant Leaf Disease Detection and Classification using Multiclass SVM Classifier

Version (884 KB) by Manu BN
A Matlab code to detect and classfy diseases in plant leaves using a multiclass SVM classifier


Updated 23 Feb 2016

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A Matlab code is written to classify the leaves into one of the following types: 'Alternaria Alternata', 'Anthracnose', 'Bacterial Blight', 'Cercospora Leaf Spot' and 'Healthy Leaves'. Classification is done by Multiclass SVM (one vs. all)
How to run??
1. Place the folder 'Leaf_Disease_Detection_code' in the Matlab path, and add all the subfolders into that path
2. Run DetectDisease_GUI.m
3. In the GUI click on Load Image and load the image from Manu's Disease Dataset, click Enhance Contrast.
4. Next click on Segment Image, then enter the cluster no containing the ROI, i.e only the disease affected part or the healthy part
5. Click on classification results. Then measure accuracy (In this case Healthy vs All diseases).
The code is loosely based on the following paper, please cite the below and give credit to the authors:
[1] Akhtar, Asma, et al. "Automated Plant Disease Analysis (APDA): Performance Comparison of Machine Learning Techniques." Frontiers of Information Technology (FIT), 2013 11th International Conference on. IEEE, 2013.
[2] Multiclass SVM by Anand Mishra link:
Suggestions and comments are always welcome

Thanks in advance,

Manu B.N

Cite As

Manu BN (2023). Plant Leaf Disease Detection and Classification using Multiclass SVM Classifier (, MATLAB Central File Exchange. Retrieved .

MATLAB Release Compatibility
Created with R2013a
Compatible with any release
Platform Compatibility
Windows macOS Linux

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Version Published Release Notes

A reference paper is added