Identification of Diseases in Paddy Leaves Using Texture Features and Neural Network

Authors(2) :-Shreekanth K N, Suresha M

Disease identification in agricultural field is the most challenging task. Initially experts visit the agricultural field or known farmer identifies the diseases. In the proposed work using image processing and soft computing technique disease identification has been done. RGB microscopic images transformed to HSV color model, Otsu segmentation used for segmentation by considering hue component of HSV color model. GLCM Features and feed forward back propagation neural network is used to classify the data and obtained result of 100% accuracy.

Authors and Affiliations

Shreekanth K N
Research Scholar, Department of P.G Studies and Research in Computer Science, Kuvempu University, Shankaraghatta, Shivamogga, Karnataka, India
Suresha M
Assistant Professor, Department of P.G Studies and Research in Computer Science, Kuvempu University, Shankaraghatta, Shivmogga, Karnataka, India

Disease, GLCM, Neural Network, Segmentation, Microscope Images.

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Publication Details

Published in : Volume 3 | Issue 3 | March-April 2018
Date of Publication : 2018-04-30
License:  This work is licensed under a Creative Commons Attribution 4.0 International License.
Page(s) : 565-572
Manuscript Number : CSEIT1833118
Publisher : Technoscience Academy

ISSN : 2456-3307

Cite This Article :

Shreekanth K N, Suresha M, "Identification of Diseases in Paddy Leaves Using Texture Features and Neural Network", International Journal of Scientific Research in Computer Science, Engineering and Information Technology (IJSRCSEIT), ISSN : 2456-3307, Volume 3, Issue 3, pp.565-572, March-April-2018.
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