• kota Sandeep
• Gadde Divya
• lokanatham Bhanusree
• paduchuriRohithVenkatpavan

The main objective of this research is to develop a prototype system for detecting the disease in paddy which are bacterial leaf spot, target spot, sectorial leaf spot, leaf mold disease. This paper concentrate on the image processing techniques used to enhance the quality of the image and neural network technique to classify the disease in plants. The methodology involves image acquisition, pre-processing and segmentation, analysis and classification of the paddy disease. For image segmentation we use K-means clustering method and features are computed from disease affected cluster. Features such as Contrast, Correlation, Energy, Homogeneity, Mean, Standard Deviation and Variance are extracted. The extracted features from disease cluster are given as classifier inputs to classify the disease.

The main objective of this research is to develop a prototype system for detecting the disease in paddy which are bacterial leaf spot, target spot, sectorial leaf spot, leaf mold disease. This paper concentrate on the image processing techniques used to enhance the quality of the image and neural network technique to classify the disease in plants. The methodology involves image acquisition, pre-processing and segmentation, analysis and classification of the paddy disease. For image segmentation we use K-means clustering method and features are computed from disease affected cluster. Features such as Contrast, Correlation, Energy, Homogeneity, Mean, Standard Deviation and Variance are extracted. The extracted features from disease cluster are given as classifier inputs to classify the disease.

"LEAF DISEASE DETECTION SYSTEM USING RASPBERRY-PI USING NEURAL NETWORK", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.7, Issue 4, page no.1063-1069, April-2020, Available :http://www.jetir.org/papers/JETIR2004340.pdf

"LEAF DISEASE DETECTION SYSTEM USING RASPBERRY-PI USING NEURAL NETWORK", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.7, Issue 4, page no. pp1063-1069, April-2020, Available at : http://www.jetir.org/papers/JETIR2004340.pdf