Survey on Leaf Disease Detection and Grading using Artificial Neural Network (ANN) and Fuzzy Logic

Abstract

In Horticulture, leaf sicknesses have become a difficult as it can bring about noteworthy reduction in both quality what is more, amount of agrarian yields. Therefore, robotized acknowledgment of maladies on leaves assumes a vital part in farming segment. This paper bestows a straightforward and computationally capable strategy utilized for leaf infection distinguishing proof and reviewing utilizing advanced picture handling and machine vision innovation. The proposed framework is partitioned into two stages, in first stage the plant is perceived on the premise of the elements of leaf, it incorporates pre-handling of leaf pictures, and highlight extraction taken after by Counterfeit Neural System based preparing and arrangement for acknowledgment of leaf. In second stage the infection present in the leaf is arranged, this procedure incorporates K-Implies based division of abandoned range, highlight extraction of abandoned bit and the ANN based grouping of malady. At that point the infection reviewing is done on the premise of the measure of infection present in the leaf.