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

Authors

  • 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

Keywords:

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

Abstract

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.

References

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IInternational Journal of Scientific Research in Computer Science, Engineering and Information Technology

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Published

2018-04-30

Issue

Volume 3, Issue 3, March-April-2018

Section

Research Articles

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This work is licensed under a Creative Commons Attribution 4.0 International License.

How to Cite

[1]
Shreekanth K N, Suresha M, " Identification of Diseases in Paddy Leaves Using Texture Features and Neural Network, IInternational 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.