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Image Based Plant Leaf Disease Recognition and Estimation System

Sheela N1 , Harsha B M2 , Nikhil Shastri3 , Gurudatt Bhat4

Section:Research Paper, Product Type: Journal Paper
Volume-7 , Issue-6 , Page no. 725-731, Jun-2019

CrossRef-DOI:   https://doi.org/10.26438/ijcse/v7i6.725731

Online published on Jun 30, 2019

Copyright © Sheela N, Harsha B M, Nikhil Shastri, Gurudatt Bhat . 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: Sheela N, Harsha B M, Nikhil Shastri, Gurudatt Bhat, “Image Based Plant Leaf Disease Recognition and Estimation System,” International Journal of Computer Sciences and Engineering, Vol.7, Issue.6, pp.725-731, 2019.

MLA Style Citation: Sheela N, Harsha B M, Nikhil Shastri, Gurudatt Bhat "Image Based Plant Leaf Disease Recognition and Estimation System." International Journal of Computer Sciences and Engineering 7.6 (2019): 725-731.

APA Style Citation: Sheela N, Harsha B M, Nikhil Shastri, Gurudatt Bhat, (2019). Image Based Plant Leaf Disease Recognition and Estimation System. International Journal of Computer Sciences and Engineering, 7(6), 725-731.

BibTex Style Citation:
@article{N_2019,
author = {Sheela N, Harsha B M, Nikhil Shastri, Gurudatt Bhat},
title = {Image Based Plant Leaf Disease Recognition and Estimation System},
journal = {International Journal of Computer Sciences and Engineering},
issue_date = {6 2019},
volume = {7},
Issue = {6},
month = {6},
year = {2019},
issn = {2347-2693},
pages = {725-731},
url = {https://www.ijcseonline.org/full_paper_view.php?paper_id=4620},
doi = {https://doi.org/10.26438/ijcse/v7i6.725731}
publisher = {IJCSE, Indore, INDIA},
}

RIS Style Citation:
TY - JOUR
DO = {https://doi.org/10.26438/ijcse/v7i6.725731}
UR - https://www.ijcseonline.org/full_paper_view.php?paper_id=4620
TI - Image Based Plant Leaf Disease Recognition and Estimation System
T2 - International Journal of Computer Sciences and Engineering
AU - Sheela N, Harsha B M, Nikhil Shastri, Gurudatt Bhat
PY - 2019
DA - 2019/06/30
PB - IJCSE, Indore, INDIA
SP - 725-731
IS - 6
VL - 7
SN - 2347-2693
ER -

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Abstract

Agriculture is the back-bone of country`s economy, where farmer`s source of income widely depends upon farming. During the cultivation of crops, it is required to properly monitor and due to change in atmospheric condition or the loss of soil nutrition these crops get encountered with certain type of diseases. Health monitoring and disease detection on plants is very critical for sustainable agriculture. It is very difficult to monitor the plant diseases manually. It requires tremendous amount of work, expertise in the plant diseases, and also require the excessive processing time. Thus farmer cannot recognize easily because of which they incur loss in production and yield. So here we propose the system where we can detect the disease based on the leaf image and diagnose for proper medication based on the result.

Key-Words / Index Term

felzenszwalb, Quickshift, color based segmentation, ResNet, LeNet, Estimation

References

[1] Anksha Rastogi, RitikaArora and ShanuSharma,” Leaf Disease Detection and Grading using ComputerVision Technology &Fuzzy Logic”
[2] RatihKartika Dewi and R. V. Hari Ginardi,”Feature -Extraction for Identificationof Sugarcane rust disease
[3] Yuan Tian,Chunjiang Zhao, Shenglian Lu and XinyuGuo,” SVM- based Multiple Classifier System for Recognition of Wheat Leaf Diseases
[4] SmitaNaikwadi, NiketAmoda,” Advances In Image Processing For Detection Of Plant Diseases”