Author : M.Thiruselvi 1
Date of Publication :7th February 2017
Abstract: Agriculture has been the prime occupation of India. Our country stands one among the major producers of many food crops in the world. But there are few declining factors like plant infection that reduce yield. Most plant diseases are caused by micro organisms. In the current scenario, the infected plants are identified through naked eye and treated manually which is inefficient. The proposed project uses image processing to detect and diagnose the diseases. Each disease has different symptoms, which is identified here with the help of GLCM and Clustering algorithm. The disease is identified and the pesticide to be used is displayed with the help of a LCD display thus reducing the effort of farmers in identifying the disease and finding the correct pesticide to be used. This ultimately increases the yield and quality of crops in a long term as soil damage is also reduced.
 J.D. Pujari, R. Yakkundimath, and A.S. Byadgi, "Image Processing Based Detection of Fungal Diseases in Plants," in Proc. International Conference on Information and Communication Technologies, India, 2015, pp. 1802–1808.
 S.K. Pilli, B. Nallathambi, S.J. George, and V. Diwanji, "eAGROBOTA Robot for Early Crop Disease Detection using Image Processing," in Proc. IEEE International Conference on Electronics and Communication Systems, India, 2014.
 R. Oberti, M. Marchi, P. Tirelli, A. Calcante, M. Iriti, and A.N. Borghese, "Automatic detection of Powdery mildew on grapevine leaves by image analysis: Optimal view-angle range to increase the sensitivity," Computers and Electronics in Agriculture, vol. 104, pp. 1-8, June 2014.
 T. Rumpf, A.K. Mahlein, U. Steiner, E.C. Oerke, H.W. Dehne, and L. Plümer, "Early detection and classification of plant diseases with Support Vector Machines based on hyperspectral reflectance," Computers and Electronics in Agriculture, vol. 74, no. 1, pp. 91-99, Oct. 2010.
 N.Otsu, "A Threshold Selection Method from GrayLevel Histograms," IEEE Transactions on Systems, Man, and Cybernetics, vol. 9, No. 1, pp. 62-66, Jan. 1979.
 Surende Kumar, Rupinder Kaur, “Plant disease detection using Image processing- Review”, International Journal of Computer Applications(0975- 8887), Volume 124- No.16, August 2015.
 Sanjay B. Dhaygude, Nitin P. Kumbhar, “Agricultural plant leaf disease setection using Image processing”, International Journal of Advanced Research in Electrical, Electronics and Instrumentation Engineering(ISSN: 2278- 8875), Vol. 2, Issue 1, January 2013.
 V. Surenderbabu, C.P. Sumathi, E. Umapathy, “Detection of Rice Leaf Diseases Using Chaos and Fractal Dimension in Image Processing”, International Journal on Computer Science and Engineering (IJCSE), ISSN : 0975-3397 Vol. 6 No. 01 Jan 2014.
 Khushal Khairnar, Rahul Dagade, “Disease detection and diagnosis on plant using image processing – A Review” , International Journal of Computer Applications (0975 – 8887) Volume 108 – No. 13, December 2014.
Y.Sanjana, AshwathSivasamy, SriJayanth, “Plant Disease Detection Using Image Processing Techniques”, International Journal of Innovative Research in Science, Engineering and Technology (An ISO 3297: 2007 Certified Organization) Vol. 4, Special Issue 6, May 2015