Detection of Leaf Disease Using Feature Extraction for Android Based System

Authors

  • Dixit Ekta Gajanan  Department of Computer Engineering, Gokhale Education Society's R. H. Sapat College of Engineering, Management Studies and Research, Nashik, Maharashtra, India
  • Gavit Gayatri Shankar  Department of Computer Engineering, Gokhale Education Society's R. H. Sapat College of Engineering, Management Studies and Research, Nashik, Maharashtra, India
  • Gode Vidya Keshav  Department of Computer Engineering, Gokhale Education Society's R. H. Sapat College of Engineering, Management Studies and Research, Nashik, Maharashtra, India

Keywords:

Image Processing, Intelligent System, Molecular Analyses, Plant Diseases, Smart Phone.

Abstract

Although professional agriculture engineers are responsible for the recognition of plant diseases, intelligent systems can be used for their diagnosis in early stages. The expert systems that have been proposed in the literature for this purpose, are often based on facts described by the user or image processing of plant photos in visible, infrared, light etc. The recognition of a disease can often be based on symptoms like lesions or spots in various parts of a plant. The color, area and the number of these spots can determine to a great extent the disease that has mortified a plant. Higher cost molecular analyses and tests can follow if necessary. This application can easily be extended for different plant diseases and different smart phone platforms.

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International Journal of Scientific Research in Science and Technology

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Published

2018-02-28

Issue

Volume 4, Issue 2, January-February-2018

Section

Research Articles

License

Copyright (c) IJSRST

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

How to Cite

[1]
Dixit Ekta Gajanan, Gavit Gayatri Shankar, Gode Vidya Keshav, " Detection of Leaf Disease Using Feature Extraction for Android Based System, International Journal of Scientific Research in Science and Technology(IJSRST), Online ISSN : 2395-602X, Print ISSN : 2395-6011, Volume 4, Issue 2, pp.450-456, January-February-2018.