International Journal For Multidisciplinary Research

E-ISSN: 2582-2160     Impact Factor: 9.24

A Widely Indexed Open Access Peer Reviewed Multidisciplinary Bi-monthly Scholarly International Journal

Call for Paper Volume 6 Issue 6 November-December 2024 Submit your research before last 3 days of December to publish your research paper in the issue of November-December.

Implementation of Plant Leaf Disease Detection using K-means Clustering and Neural Networks

Author(s) DARSHAN P R, DEEPASHREE S C, DEEPA R, POORNIMA B P
Country India
Abstract Plants exist all over the place; we live, as well as places without us. Plant disease is one of the essential causes that reduces quantity and degrades quality of the agricultural merchandises. Plant diseases have turned into a terrible as it can cause significant reduction in both quality and quantity of agricultural products. Images form important data and information in biological sciences. Until recently photography was the only method to reproduce and report such data. It is difficult to quantify or treat the photographic data mathematically. This project, classifies the plant leaves and stems at hand into infected and non-infected classes. The developing software provides a fast and accurate method in which the leaf diseases are detected and classified using k-means based segmentation and neural networks-based classification. Most common diseases seen in the leaves of Tapioca and Mango are discussed here for this approach. In this paper, respectively, the applications of K-means clustering and Neural Networks (NNs) have been formulated for clustering and classification of diseases that effect on plant leaves. Recognizing the disease is mainly the purpose of the proposed approach. Thus, the proposed Algorithm was tested on five diseases which influence on the plants; they are: Early scorch, Cottony mold, ashen mold, late scorch, tiny whiteness. The experimental results indicate that the proposed approach is a valuable approach, which can significantly support an accurate detection of leaf diseases in a little computational effort. This project gives 95% of efficiency using MATLAB simulation results.
Keywords Keywords: Leaf, K-means clustering and Neural Networks, RGB, HIS
Field Computer Applications
Published In Volume 5, Issue 6, November-December 2023
Published On 2023-12-19
Cite This Implementation of Plant Leaf Disease Detection using K-means Clustering and Neural Networks - DARSHAN P R, DEEPASHREE S C, DEEPA R, POORNIMA B P - IJFMR Volume 5, Issue 6, November-December 2023. DOI 10.36948/ijfmr.2023.v05i06.10700
DOI https://doi.org/10.36948/ijfmr.2023.v05i06.10700
Short DOI https://doi.org/gs9kzz

Share this