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CrossRefDOI
ESTD2016
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AccessOpen
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Paper Title
Plant leaf disease classification using image processing
Authors
Anusha , Sharan L Pais
Keywords
Abstract
Indian economy is highly depend on the agricultural products. Therefore detecting disease of plants at the earlier stage plays important role. To detect diseases, requires enormous amount of work, mastery in the leaf diseases, and additionally need the extreme amount of time.Image processing is a diverging area where researches and advancements are taking a geometrical progress in the agricultural field. Identification of plant diseases can not only maximize the yield production but also can be supportive for varied types of agricultural practices.Plant leaf disease detection and identification includes the stages like image acquisition, image pre-processing, image segmentation, feature extraction and classification.This paper discusses techniques for image pre-processing, image segmentation algorithm used for automatic recognition and research on various plant leaf disease classification algorithms that may be used for leaves disease classification.
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IJRTI — journal style
"Plant leaf disease classification using image processing", IJRTI - International Journal for Research Trends and Innovation (www.ijrti.org), ISSN:2456-3315, Vol.4, Issue 5, page no.158 - 162, May-2019, Available :https://ijrti.org/papers/IJRTI1905038.pdf
APA — 7th edition
Anusha, & Pais, S. L. (2019). Plant leaf disease classification using image processing. International Journal for Research Trends and Innovation, 4(5), 158 - 162. https://ijrti.org/viewpaperforall.php?paper=IJRTI1905038
MLA — 9th edition
Anusha, and Sharan L Pais. "Plant leaf disease classification using image processing." International Journal for Research Trends and Innovation, vol. 4, no. 5, 2019, pp. 158 - 162, https://ijrti.org/viewpaperforall.php?paper=IJRTI1905038.
Chicago — 17th, bibliography
Anusha, and Sharan L Pais. "Plant leaf disease classification using image processing." International Journal for Research Trends and Innovation 4, no. 5 (2019): 158 - 162. https://ijrti.org/viewpaperforall.php?paper=IJRTI1905038.
Harvard — author–date
Anusha and Pais, S.L. (2019) 'Plant leaf disease classification using image processing', International Journal for Research Trends and Innovation, 4(5), pp. 158 - 162. Available at: https://ijrti.org/viewpaperforall.php?paper=IJRTI1905038
IEEE — numbered reference
Anusha and S. L. Pais, "Plant leaf disease classification using image processing," IJRTI, vol. 4, no. 5, pp. 158 - 162, May. 2019.
Vancouver — biomedical
Anusha, Pais SL. Plant leaf disease classification using image processing. IJRTI. 2019 May;4(5):158 - 162.
AMA — 11th edition
Anusha, Pais SL. Plant leaf disease classification using image processing. IJRTI. 2019;4(5):158 - 162. Accessed at https://ijrti.org/viewpaperforall.php?paper=IJRTI1905038
BibTeX — Zotero, Mendeley, LaTeX
@article{IJRTI1905038,
author = {Anusha and Sharan L Pais},
title = {Plant leaf disease classification using image processing},
journal = {International Journal for Research Trends and Innovation},
volume = {4},
number = {5},
pages = {158 - 162},
year = {2019},
month = {May},
issn = {2456-3315},
url = {https://ijrti.org/viewpaperforall.php?paper=IJRTI1905038}
}
RIS — EndNote, RefWorks
TY - JOUR
AU - Anusha
AU - Pais, Sharan L
TI - Plant leaf disease classification using image processing
T2 - International Journal for Research Trends and Innovation
JA - IJRTI
VL - 4
IS - 5
PY - 2019
SN - 2456-3315
UR - https://ijrti.org/viewpaperforall.php?paper=IJRTI1905038
SP - 158
EP - 162
ER -
Issue
Volume 4 Issue 5,
May-2019
Pages : 158 - 162
Other Publication Details
Paper Reg. ID
IJRTI_180890
Published Paper ID
IJRTI1905038
Downloads
205,645
Research Area
Engineering
Country
Udupi, Karnataka , India
Published
May 2019
Published Paper PDF
https://ijrti.org/papers/IJRTI1905038.pdf
Published Paper URL
https://ijrti.org/viewpaperforall.php?paper=IJRTI1905038
About Publisher
International Journal for Research Trends and Innovation
Published by IJRTI (JW Publication)
2456-3315
ISSN
10.57
Impact Factor
2016
ESTD Year
Open
Access
Impact Factor 10.57 calculated by Google Scholar and Semantic Scholar.
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Declarations
Funding
No external funding was received for this study.
Conflict of Interest
The authors declare that they have no conflict of interest.
Acknowledgements
The authors would like to thank the reviewers and the editorial board of International Journal for Research Trends and Innovation for their careful reading and constructive comments, and all colleagues who supported the preparation of this manuscript.
