Disease Detection on Leaf using Image Processing |
Author(s): |
| Sachin Gobbur , JSCOE Hadapsar Pune; Sharad Ghallal, JSCOE Hadapsar Pune; Akash Jadhav, JSCOE Hadapsar Pune; Yogesh Khandare, JSCOE Hadapsar Pune |
Keywords: |
| Leaf Disease, Image Processing, Java |
Abstract |
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In agriculture research of automatic leaf disease detection is essential research topic as it may prove benefits in monitoring large fields of crops, and thus automatically detect symptoms of disease as soon as they appear on plant leaves. There are the main steps for disease detection of Image Acquisition, Image Preprocessing, Image Segmentation, Feature Extraction and Statistical Analysis. This proposed work is in first image filtering using median filter and convert the RGB image to CIELAB color component, in second step image segmented using the k-medoid technique, in next step masking green-pixels & Remove of masked green pixels, after in next step calculate the Texture features Statistics, in last this features passed in neural network. The Neural Network classification performs well and could successfully detect and classify the tested disease. |
Other Details |
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Paper ID: IJSRDV6I20041 Published in: Volume : 6, Issue : 2 Publication Date: 01/05/2018 Page(s): 309-311 |
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