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Diseases Identification in Plants Using K-Means Algorithm

M. Krishnamoorthy1 , A. Noble Mary Juliet2 , C. Keerthana3 , R. Usha Nandhini4

Section:Survey Paper, Product Type: Journal Paper
Volume-7 , Issue-2 , Page no. 458-462, Feb-2019

CrossRef-DOI:   https://doi.org/10.26438/ijcse/v7i2.458462

Online published on Feb 28, 2019

Copyright © M. Krishnamoorthy, A. Noble Mary Juliet, C. Keerthana, R. Usha Nandhini . 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: M. Krishnamoorthy, A. Noble Mary Juliet, C. Keerthana, R. Usha Nandhini, “Diseases Identification in Plants Using K-Means Algorithm,” International Journal of Computer Sciences and Engineering, Vol.7, Issue.2, pp.458-462, 2019.

MLA Style Citation: M. Krishnamoorthy, A. Noble Mary Juliet, C. Keerthana, R. Usha Nandhini "Diseases Identification in Plants Using K-Means Algorithm." International Journal of Computer Sciences and Engineering 7.2 (2019): 458-462.

APA Style Citation: M. Krishnamoorthy, A. Noble Mary Juliet, C. Keerthana, R. Usha Nandhini, (2019). Diseases Identification in Plants Using K-Means Algorithm. International Journal of Computer Sciences and Engineering, 7(2), 458-462.

BibTex Style Citation:
@article{Krishnamoorthy_2019,
author = {M. Krishnamoorthy, A. Noble Mary Juliet, C. Keerthana, R. Usha Nandhini},
title = {Diseases Identification in Plants Using K-Means Algorithm},
journal = {International Journal of Computer Sciences and Engineering},
issue_date = {2 2019},
volume = {7},
Issue = {2},
month = {2},
year = {2019},
issn = {2347-2693},
pages = {458-462},
url = {https://www.ijcseonline.org/full_paper_view.php?paper_id=3687},
doi = {https://doi.org/10.26438/ijcse/v7i2.458462}
publisher = {IJCSE, Indore, INDIA},
}

RIS Style Citation:
TY - JOUR
DO = {https://doi.org/10.26438/ijcse/v7i2.458462}
UR - https://www.ijcseonline.org/full_paper_view.php?paper_id=3687
TI - Diseases Identification in Plants Using K-Means Algorithm
T2 - International Journal of Computer Sciences and Engineering
AU - M. Krishnamoorthy, A. Noble Mary Juliet, C. Keerthana, R. Usha Nandhini
PY - 2019
DA - 2019/02/28
PB - IJCSE, Indore, INDIA
SP - 458-462
IS - 2
VL - 7
SN - 2347-2693
ER -

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Abstract

The detection of leaf is a very important factor to prevent serious outbreak. Automatic detection of plant disease is essential. Most plant diseases are caused by fungi, bacteria, and viruses. Fungi are identified primarily from their morphology, with emphasis placed on their reproductive structures. Bacteria are considered more primitive than fungi and generally have simpler life cycles. With few exceptions, bacteria exist as single cells and increase in numbers by dividing into two cells during a process called binary fission. Viruses are extremely tiny particles consisting of protein and genetic material with no associated protein. The term disease is usually used only for the destruction of live plants. The developed processing scheme consists of four main steps, first a color transformation structure for the input RGB image is created, and this RGB is converted to HSI because RGB is for color generation and for color descriptor. Then green pixels are masked and removed using specific threshold value, then the image is segmented and the useful segments are extracted. Finally the presence of diseases on the plant leaf is evaluated.

Key-Words / Index Term

Noise removal, Segmentation, clustering, pre-processing

References

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