Detection of Affected Part of Plant Leaves and Classification of Diseases Using CNN TechniqueJournal: International Journal of Engineering and Techniques (Vol.4, No. 2)
Publication Date: 2018-04-25
Authors : A.Blessy D.C. Joy Winnie Wise;
Page : 823-829
Keywords : Leaf disease; Fuzzy C-means clustering; GLCM; Convolution Neural Network;
Plant pathology is the scientific study of plant diseases caused by pathogens and environmental conditions. It includes pathogen identification, diseases cycles, economic impact, management of plant diseases, etc. In existing, to detect the diseases they used the spectroscopic techniques. These techniques are very expensive and can only be utilized by trained persons only. This project presents the detection of diseases which are detected using CNN (ConvolutionNeuralNetwork) technique. First the sample leaf image is given as input. Then, color channels are separated from the leaf image from these the green pixels are masked from the original image. The masking is done to avoid the processing of the green area of the leaves, since, it is healthy. By removing the green area from the original area the remaining infected area is calculated. Then the features are extracted from the affected area. Finally these features are given to the CNN to classify the disease. After finding the disease the solution for those diseases are send the corresponding user mobile using GSM device.
Other Latest Articles
Last modified: 2018-07-06 20:13:57