Plant Leaf Disease Detection and Classification using Multiclass SVM Classifier
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: http://www.mathworks.com/matlabcentral/fileexchange/33170-multi-class-support-vector-machine
Suggestions and comments are always welcome
Thanks in advance,
Manu B.N
Citation pour cette source
Manu BN (2024). Plant Leaf Disease Detection and Classification using Multiclass SVM Classifier (https://www.mathworks.com/matlabcentral/fileexchange/55098-plant-leaf-disease-detection-and-classification-using-multiclass-svm-classifier), MATLAB Central File Exchange. Récupéré le .
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- AI, Data Science, and Statistics > Deep Learning Toolbox > Image Data Workflows > Pattern Recognition and Classification >
- Sciences > Food Sciences >
- Sciences > Earth, Ocean, and Atmospheric Sciences > Environmental Science >
- Image Processing and Computer Vision > Image Processing Toolbox > Image Filtering and Enhancement > Deblurring >
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Version | Publié le | Notes de version | |
---|---|---|---|
1.0.0.0 | A reference paper is added |