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A novel segmentation method for classification of Diseased and Healthy Maize and Paddy Leaves Using OCLBP

T. Harisha Naik1 , M. Suresha2

Section:Research Paper, Product Type: Journal Paper
Volume-6 , Issue-12 , Page no. 330-334, Dec-2018

CrossRef-DOI:   https://doi.org/10.26438/ijcse/v6i12.330334

Online published on Dec 31, 2018

Copyright © T. Harisha Naik, M. Suresha . 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: T. Harisha Naik, M. Suresha, “A novel segmentation method for classification of Diseased and Healthy Maize and Paddy Leaves Using OCLBP,” International Journal of Computer Sciences and Engineering, Vol.6, Issue.12, pp.330-334, 2018.

MLA Style Citation: T. Harisha Naik, M. Suresha "A novel segmentation method for classification of Diseased and Healthy Maize and Paddy Leaves Using OCLBP." International Journal of Computer Sciences and Engineering 6.12 (2018): 330-334.

APA Style Citation: T. Harisha Naik, M. Suresha, (2018). A novel segmentation method for classification of Diseased and Healthy Maize and Paddy Leaves Using OCLBP. International Journal of Computer Sciences and Engineering, 6(12), 330-334.

BibTex Style Citation:
@article{Naik_2018,
author = {T. Harisha Naik, M. Suresha},
title = {A novel segmentation method for classification of Diseased and Healthy Maize and Paddy Leaves Using OCLBP},
journal = {International Journal of Computer Sciences and Engineering},
issue_date = {12 2018},
volume = {6},
Issue = {12},
month = {12},
year = {2018},
issn = {2347-2693},
pages = {330-334},
url = {https://www.ijcseonline.org/full_paper_view.php?paper_id=3338},
doi = {https://doi.org/10.26438/ijcse/v6i12.330334}
publisher = {IJCSE, Indore, INDIA},
}

RIS Style Citation:
TY - JOUR
DO = {https://doi.org/10.26438/ijcse/v6i12.330334}
UR - https://www.ijcseonline.org/full_paper_view.php?paper_id=3338
TI - A novel segmentation method for classification of Diseased and Healthy Maize and Paddy Leaves Using OCLBP
T2 - International Journal of Computer Sciences and Engineering
AU - T. Harisha Naik, M. Suresha
PY - 2018
DA - 2018/12/31
PB - IJCSE, Indore, INDIA
SP - 330-334
IS - 12
VL - 6
SN - 2347-2693
ER -

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Abstract

In this paper we have proposed a novel segmentation method for classification of diseased and healthy maize and paddy leaves using Opposite Color Local Binary Pattern (OCLBP). The proposed works have been done on the maize and paddy leaves, the dataset has the diseased and healthy leaves, diseased leaves have the yellowish brown patches. Disease in maize and paddy leaves may be due to biotic causes. Generally, leaves spotted with yellow at initial stage and appear bronzed brown color at end stage at its disease levels. The diseased spots are all having color transition from yellow to Bronzed brown color. This yellow to bronzed brown color transition is appeared in between red and green colors of RGB color cube. This color transition motivated us to use OCLBP as a segmentation tool. The OCLBP textured image is the image of segmented diseased part which helps in extract the features. So here considered red color channel against green color channels to get the OCLBP textured image. SVM is used for diseased and heathy leaves classification. We have attempted to introduce the best segmentation, feature selection and dimensionality approaches for image texture which support fast and accurate pattern recognition and object identification.

Key-Words / Index Term

Feature Selection, Local Binary Pattern, Gabor features, OCLBP

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