Statistical analysis of RGB and Edge detection model in detection of plant diseases
Alt Text: RGB and Edge Detection Model Analysis for Plant Diseases
Title: Statistical Analysis of RGB and Edge Detection Model in Detection of Plant Diseases
Caption: An analytical comparison of RGB and Edge Detection Models in plant disease detection.
Description: Explore the performance of RGB and Edge Detection models in detecting plant diseases using real datasets.
International Journal of Computer Techniques – Volume 12 Issue 2, April 2025
Shruti Saini1, Sugandh Raghav1, Dr. Shivani Saxena2
1Department of Electronics, Banasthali Vidyapith, Banasthali, Rajasthan
2Assistant Professor, Department of Electronics, Banasthali Vidyapith, Rajasthan
Email: shivani.saxena@banasthali.in
Abstract
The proposed work aims to analyse RGB and edge detection model in detection of plant disease using different plant datasets taken from Kaggle. MATLAB is used for stimulation and extracting features from plant images. The MATLAB machine learning toolbox is employed to train RGB and edge detection models for different plants. The performance of models is evaluated using a confusion matrix and ROC curve, determining the superior model for plant training. Accuracy of the models on different plants is also evaluated. Experimental results demonstrate that the proposed model effectively detects and classifies plant diseases. Future work will aim to recommend suitable fertilizers, increasing crop yield and offering healthier produce to consumers.
Keywords
RGB Model, Edge Detection, Plant Diseases, MATLAB, Machine Learning, Plant Classification
Conclusion
Major sources of food for human beings are plants, and a significant population in India depends on farming. This underscores the need for early detection of plant leaf diseases. The main aim of this study is to introduce technology in agriculture and automate plant disease detection. The experimental results propose that the model effectively detects and classifies plant diseases. In future, the work can support farmers in determining suitable fertilizers, improving crop health, increasing yield, and providing healthier crops to consumers.
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How to Cite
Shruti Saini, Sugandh Raghav, Dr. Shivani Saxena, “Statistical Analysis of RGB and Edge Detection Model in Detection of Plant Diseases,” International Journal of Computer Techniques, Volume 12, Issue 2, April 2025. ISSN 2394-2231.
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