Digital Image Processing-An Elegant Technology to Perceive Diseases in Plants
Keywords:
Fungus, DIP, ED, ThresholdAbstract
Agricultural production quality and quantity can be enhanced using precision agriculture. In India, many plants used as medicine as well as their flowers for decoration and worship. Significant threats to production of such crops are affected by various diseases and hard to control. The fungus is one of the disorders which is commonly and mostly affects these plans. Symptoms of fungus on leaves are different as tan or different colored spots like yellow, brown with low to high infection intensity. The fungus produces chemicals which are harmful to plant growth as well as affects the human health [3]. The fungal disease causes plants to die prematurely and need to detect. That can avoid the distortion of these valuable plants and all its parts. The emergence of Digital Image Processing is helpful in precision agriculture. With the various processing of these plant images, it is possible to detect the plant disease. The research proposes the model to identify the fungus infection of Lotus Leaf.
References
Erick D Wolf, James Shroyer, and Brian Olson, "Wheat disease identification" NCERA-184 and WERA-97, Kansas State University.
Jagadeesh D. Pujari, Rajesh, Abdul Munaf, Syedhusain Byadgi, "SVM & ANN based classification of plant diseases Using Feature Reduction Technique" International Journal of IM&AI ( Interactive Multimedia and Artificial Intelligence), Yr. 2016.
Manisha Kaushal, Arjan Singh, Baljit Singh, "Adaptive Thresholding for Edge Detection in Gray Scale Images" International Journal of Engineering Science and Technology Volume 2(6), 2010, 2077-2082, ISSN: 0975-5462, pp. 2077- 2082.
The clinic University of Nebraska,"Plant and Pest Diagnostic" Clinic University of Nebraska-Lincoln 448 Plant Sciences Hall Lincoln, NE 68583-0722 (402) 472-2559, Department of Agriculture (USDA). March 2011
R. C. Gonzalez and R.E. Woods, "Digital Image Processing" Addison-Wesley, New York (2005).
R. Maheswaran, S. Muruganand, and C. Hemalatha, "Hybrid Embedded System Design for Real-time Monitoring Growth & Detection of Diseases in Oryza Sativa and Triticum Aestivum" International Conference on Interdisciplinary Research in Engineering and Technology -2015, pp-23-32.
Sanjay B. Dhaygude, Mr.Nitin P.Kumbhar,"Agricultural plant Leaf Disease Detection Using Image Processing" International Journal of Advanced Research in EEIE (Advanced Research in Electrical, Electronics and Instrumentation Engineering), Volume 2, Issue 1, January 2013
Sarika Datir, “Monitoring and Detection of Agricultural Disease using Wireless Sensor Network” International Journal of Computer Applications, February 2014, ISSN:0975 – 8887, Volume-87, Issue-4
Shitala Prasad, Piyush Kumar, “Plant Leaf Disease Detection Using Gabor Wavelet Transform” SEMCCO 2012, LNCS 7677, pp. 372–379, 2012, Springer-Verlag Berlin Heidelberg 2012
Supriya S. Patki, Dr. G. S. Sable, “Cotton Leaf Disease Detection” IOSR Journal of VLSI and Signal Processing (IOSR-JVSP) Volume 6, Issue-3, Ver-I -May-Jun 2016.
S. Manimegalai, “Apple Leaf Disease Identification using Support Vector Machine” International Conference on Emerging Trends in Applications of Computing ( IC ETAC 2K17 ), pp. 1-4, ISSN: 2394-2231
Tirath Sahu, Yogendra Jain "Improved Simplified Novel Method for Edge Detection in Grayscale Images using adaptive Thresholding" Journal of Advances in Computer Networks, Volume 3, No. 2, June 2015, DOI: 10.7763/JACN.2015.V3.159, pp. 157-161
Downloads
Published
How to Cite
Issue
Section
License

This work is licensed under a Creative Commons Attribution 4.0 International License.
Authors contributing to this journal agree to publish their articles under the Creative Commons Attribution 4.0 International License, allowing third parties to share their work (copy, distribute, transmit) and to adapt it, under the condition that the authors are given credit and that in the event of reuse or distribution, the terms of this license are made clear.