High Impact Factor : 4.396 icon | Submit Manuscript Online icon |

Compuer Based Framework for Identification of Leaf Diseases and Risk Assessment


Rajan Mani , Sam Higginbottom University of Agriculture, Technology and Sciences Allahabad, India; Ashish Ratn Mishra, Sam Higginbottom University of Agriculture, Technology and Sciences Allahabad, India


Leaf Disease Detection; Image Processing; Maple; Machine Learning


Leaf diseases can potentially decrease quality as well as quantity of yields in agricultural sector. Diseases on leaf usually slow down the productivity of the plants, so how we will able to detect the leaf diseases before it affects the productivity. Current systems of leaf disease identification have no direct automated methodologies rather identified by naked eyes test. However, this technique is not so efficient in terms of identification time as well as accuracy in distinguishing various types of diseases. Maple leaves exhibits variety of diseases. So to find the leaf disease computer base systems are required. In this way several techniques are used which help in finding the leaf diseases. Leaf disease identification as well as estimation of the spread of disease in individual leaf is a known problem. Several methods are discovered so far such as digital image processing, classification, clustering, and each technique have several algorithms that produce good results respectively in variety of domains. To make the result more effective digital Image processing based automated computer based framework can alter the situation significantly by playing an accurate expert in doing so and hence, saving time as well as cost. Thus, prime objective of the proposed work is to develop a DIP and machine learning based automated disease identification in maple leaves. Moreover, the proposed system calculates affected area too.

Other Details

Paper ID: IJSRDV7I50419
Published in: Volume : 7, Issue : 5
Publication Date: 01/08/2019
Page(s): 801-805

Article Preview

Download Article