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Leaf Disease Detection Using Image Processing and Machine Learning

Author(s):

Sonali Sahebrao Sangle , Sir Visvesvaraya Institute Of Technology, Chincholi; Mayuri Warungase, SVIT, Chincholi; Sumedha Ugale, SVIT, Chincholi; Snehal Tajane, SVIT, Chincholi; Prof. Sharad Rokade, SVIT, Chincholi

Keywords:

Agriculture, Leaf Diseases, Image Segmentation, Extraction, K-Mean Cluster, SVM Classifier, Android Application

Abstract

In development of India agriculture is the major economic factor. Indian people are highly dependent on agriculture. In agriculture disease detection is one of the most important factors huge times as well as skilled labour are also required. As we know the agricultural sector plays an important role in the economy of a country, as there are many different varieties of crops available to farmers. However, difficulties occur when the crops get infected by some kind of disease, and the farmers are not informed of the disease at the correct moment. Farmers do not know what disease they are dealing with when they detect the disease. For this reason, the study of leaf disease detection in agriculture is a fundamental subject of study as it could prove useful in the observation of vast fields of crops. In this paper we are going to detect the different diseases occurring on plants using image processing and machine learning. In image processing there several steps to determined diseases such as image collection, image segmentation, feature extraction, classification. And in addition, we are going to develop an application to control water pump from the android application to avoid overflow of water so that water will not be wasted.

Other Details

Paper ID: IJSRDV10I10186
Published in: Volume : 10, Issue : 1
Publication Date: 01/04/2022
Page(s): 97-99

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