Plant Pathology Disclosure

EasyChair Preprint 9643, version 2

Abstract

Farming is a ccrusial sector of Indian economy. In order to boost output yield, the agricultural industry must overcome a number of obstacles, including an illness brought on by microbes, infections and organism. The manual monitoring, observation, or treatment of plant diseases is an extremely difficult undertaking. A quick and inventive technique is required to diagnose a plant early, and farmers would profit from a system that recommends plants. Therefore, this is the ideal time to develop disease evalution methods that could be helpful for the current agricultural productivity. the current method for detecting disease utilising a computer vision technique can only do so after the sickness has already manifested itself. Therefore, this application is built on two techniques: first, deep learning for disease diagnosis and recognition, and second, image processing techniques linked to machine learning (ML). Using machine learning algorithms, which comprise procedures like dataset consstruction, loading images, prepping, segmentation, feature extraction, training a classifier, and classification, it is possible to classify plant disease. several diseases deplete the chlorophyll in leaves, which result in brown or black spot on the surface of the leaf. These can be found out utilising machine learning methods for classification, feature extraction, image preprocessing, and image segmentation. For feature extraction the Grey Level Co-occurrence Matrix (GLCM) is employed. One of the machine learning techniques used for classification is called the Support Vector Machine (SVM).

Using the researched ML/DL techniques, wer-based application development will definitely boost agricultural productivity.

Keyphrases: Digital Image Processing, Grey Level Co-occurrence Matrix, Support Vector Machine, machine learning

@booklet{EasyChair:9643,
  author    = {Pratiksha Bankar and Rucha Garud and Suraj Suryavanshi and Vaibhav Matne and Vinod Wadne},
  title     = {Plant Pathology Disclosure},
  howpublished = {EasyChair Preprint 9643},
  year      = {EasyChair, 2023}}