The week's pick
Reseach Article
Pigeon Pea Leaf Disease Classification using BoVW and DSIFT
by
G.G. Rajput,
Vanita Bhimappa Doddamani
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 186 - Number 45 |
| Year of Publication: 2024 |
| Authors: G.G. Rajput, Vanita Bhimappa Doddamani |
10.5120/ijca2024924096
|
G.G. Rajput, Vanita Bhimappa Doddamani . Pigeon Pea Leaf Disease Classification using BoVW and DSIFT. International Journal of Computer Applications. 186, 45 ( Oct 2024), 44-49. DOI=10.5120/ijca2024924096
@article{
10.5120/ijca2024924096,
author = {
G.G. Rajput,
Vanita Bhimappa Doddamani
},
title = { Pigeon Pea Leaf Disease Classification using BoVW and DSIFT },
journal = {
International Journal of Computer Applications
},
issue_date = { Oct 2024 },
volume = { 186 },
number = { 45 },
month = { Oct },
year = { 2024 },
issn = { 0975-8887 },
pages = {
44-49
},
numpages = {9},
url = {
https://ijcaonline.org/archives/volume186/number45/pigeon-pea-leaf-disease-classification-using-bovw-and-dsift/
},
doi = { 10.5120/ijca2024924096 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-10-26T00:55:48.963255+05:30
%A G.G. Rajput
%A Vanita Bhimappa Doddamani
%T Pigeon Pea Leaf Disease Classification using BoVW and DSIFT
%J International Journal of Computer Applications
%@ 0975-8887
%V 186
%N 45
%P 44-49
%D 2024
%I Foundation of Computer Science (FCS), NY, USA
Abstract
Plant diseases are continually emerging on leaves, posing a significant threat to agricultural productivity and food security in many parts of the world. Early detection and precise diagnosis of these plant diseases are essential to mitigate financial losses and environmental damage caused by misdiagnosis. In this paper, presented a feature-based approach for detecting pigeonpea leaf diseases from images. The pigeonpea (Cajanus cajan (L.) Millsp.), a member of the Fabaceae family, is a crucial legume shrub found in the semi-arid tropics and subtropics of Asia and Africa. Dense Scale-Invariant Feature Transforms (DSIFT) and Bag of Visual Words (BoVW) features are employed for feature extraction. Classification methods namely, SVM, KNN, RF, DT, XGBoost and Light GBM and CNN are used for disease classification with different combinations of DSIFT and BoVW features. Light GBM and CNN have yielded better accuracy compared to other classifiers.
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Index Terms
Computer Science
Information Sciences
Digital image processing
Machine learning
Deep learning
Keywords