Shruti Saini, Sugandh Raghav Department of Physical Sciences, Banasthali Vidyapith, Rajasthan
Dr. Shivani Saxena Assistant Professor, Department of Physical Sciences, Banasthali Vidyapith, Rajasthan
Abstract
The proposed work analyzes models trained using features extracted from RGB and edge detection methods for classification of plant leaf diseases. A dataset of various plant leaves was processed using MATLAB for simulation and feature extraction, with models trained using deep learning techniques. Accuracy and efficiency were assessed using confusion matrix and ROC curve.
Since plants are a major food source, early disease detection is crucial in agriculture. Experimental results indicate that edge detection models are more accurate for plants with sharp edges, while RGB models effectively classify various leaf types.
References
Arivazhagan S., Newlin Shebia R. (2013). Detection of unhealthy plant leaves using texture features. CIGR journal.
Sarkar, C. et al. (2023). Leaf disease detection using machine learning. Applied Soft Computing.
Post Comment