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Citrus leaf disease detection using Svm classifier
D. Sruthi,
Published in Science and Engineering Research Support Society
Volume: 28
Issue: 14
Pages: 395 - 403
Technologies are progressing, but farmers are still facing problems in identifying the plant diseases. Crop diseases are becoming a threat to the farmers due to which their crop productivity is going down. Each and every plant will be having different diseases and manual analysis of those diseases is very difficult. This calls for a huge amount of work, experience on diseases in plants and also extensive time for processing. All of these variables would reduce the productivity of crops. Image processing along with machine learning paves a way for the identification of the diseases. In this project citrus leaf disease dataset is used for identifying the diseases. K-Means Segmentation is used and inputs to the classifier. Both kNN and SVM classifiers are used out of which SVM acquired better results with an accuracy of 70.31%. © 2019 SERSC.
About the journal
JournalInternational Journal of Advanced Science and Technology
PublisherScience and Engineering Research Support Society