IoT based Automated Plant Disease Classification using Support Vector Machine
Abstract
Leaf - a significant part of the plant, produces food
using the process called photosynthesis. Leaf disease can cause
damage to the entire plant and eventually lowers crop production.
Machine learning algorithm for classifying five types of diseases,
such as Alternaria leaf diseases, Bacterial Blight, Gray Mildew,
Leaf Curl and Myrothecium leaf diseases, is proposed in the
proposed study. The classification of diseases needs front face
of leafs. This paper proposes an automated image acquisition
process using a USB camera interfaced with Raspberry PI SoC.
The image is transmitted to host PC for classification of diseases
using online web server. Pre-processing of the acquired image by
host PC to obtain full leaf, and later classification model based
on SVM is used to detect type diseases. Results were checked
with a 97% accuracy for the collection of acquired images.
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