A Review On : Plant Disease Detection Using Image Classification

Authors

  • Prof. Megha A. Patil  Assistant Professor in Department of CSE, Anuradha Engineering College, Sant Gadge baba Amravati, Chikhli, India
  • Shubham M. Pawar  Computer Science and Engineering, Anuradha Engineering College, Sant Gadge baba Amravati, Chikhli, India
  • Ankita M. Yendole  Computer Science and Engineering, Anuradha Engineering College, Sant Gadge baba Amravati, Chikhli, India

Keywords:

Disease Detection, Production Rate, Image processing, Infection Region.

Abstract

Crop cultivation plays a very important role in agriculture. The earth population is growing day by day. So, it has become important to grow a sufficient number of crops to feed such a huge population. Presently, Food is one of the basic needs of human being, the loss of food is principal because of infected crops, that reflexively reduce the assembly rate, productivity per unit space and reduction in quality of economic part of the crops, as a result of the 70-80 percent backout in yield of crops is because of diseases caused by varied micro-organisms like bacterium, virus and fungi. In this paper focus on image acquisition, image pre-processing, image segmentation, image clustering. We reviewed techniques used to detect plant diseases and provide solutions to recover from the disease different disease classification techniques that can be used for plant leaf disease detection by using image processing using K-means clustering algorithm.

References

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Published

2020-02-17

Issue

Section

Research Articles

How to Cite

[1]
Prof. Megha A. Patil, Shubham M. Pawar, Ankita M. Yendole, " A Review On : Plant Disease Detection Using Image Classification, International Journal of Scientific Research in Science and Technology(IJSRST), Online ISSN : 2395-602X, Print ISSN : 2395-6011, Volume 5, Issue 6, pp.59-63, January-February-2020.