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Paddy Leaf Disease Identification and Classification System: A Review

P. Iswarya1 , D. Maheswari2

Section:Review Paper, Product Type: Journal Paper
Volume-7 , Issue-5 , Page no. 976-979, May-2019

CrossRef-DOI:   https://doi.org/10.26438/ijcse/v7i5.976979

Online published on May 31, 2019

Copyright © P. Iswarya, D. Maheswari . This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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IEEE Style Citation: P. Iswarya, D. Maheswari, “Paddy Leaf Disease Identification and Classification System: A Review,” International Journal of Computer Sciences and Engineering, Vol.7, Issue.5, pp.976-979, 2019.

MLA Style Citation: P. Iswarya, D. Maheswari "Paddy Leaf Disease Identification and Classification System: A Review." International Journal of Computer Sciences and Engineering 7.5 (2019): 976-979.

APA Style Citation: P. Iswarya, D. Maheswari, (2019). Paddy Leaf Disease Identification and Classification System: A Review. International Journal of Computer Sciences and Engineering, 7(5), 976-979.

BibTex Style Citation:
@article{Iswarya_2019,
author = {P. Iswarya, D. Maheswari},
title = {Paddy Leaf Disease Identification and Classification System: A Review},
journal = {International Journal of Computer Sciences and Engineering},
issue_date = {5 2019},
volume = {7},
Issue = {5},
month = {5},
year = {2019},
issn = {2347-2693},
pages = {976-979},
url = {https://www.ijcseonline.org/full_paper_view.php?paper_id=4348},
doi = {https://doi.org/10.26438/ijcse/v7i5.976979}
publisher = {IJCSE, Indore, INDIA},
}

RIS Style Citation:
TY - JOUR
DO = {https://doi.org/10.26438/ijcse/v7i5.976979}
UR - https://www.ijcseonline.org/full_paper_view.php?paper_id=4348
TI - Paddy Leaf Disease Identification and Classification System: A Review
T2 - International Journal of Computer Sciences and Engineering
AU - P. Iswarya, D. Maheswari
PY - 2019
DA - 2019/05/31
PB - IJCSE, Indore, INDIA
SP - 976-979
IS - 5
VL - 7
SN - 2347-2693
ER -

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Abstract

In many of the developing countries economy greatly depend on the agricultural productivity. The most common form of detecting the plant disease infection is recognized from the leaves color and texture. The researchers with the help of information and communication enabled technology, automated the farmers traditional process of plant disease identification. To enhance the agricultural crop production, plant disease detection should be done at early stage in an automatic manner that helps in spreading the infection to other plants. This paper focus to analyze the previous studies in identifying paddy plant disease detection system. The manuscript summarizes various available paddy leaf diseases, and discusses techniques employed in the classification of healthy and infected paddy plant. The survey would help the researchers to understand the challenges involved in dataset collection and highlights several points in future research directions.

Key-Words / Index Term

Edge detection, Image processing, Internet of Things, K-means clustering and K Nearest neighbor

References

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