Fruit Disease Detection Using GLCM And SVM Classifier
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Analytics plays a critical role in detecting and analyzing the diseases. The proposed system identifies the fruits that are affected with diseases. It is done by collecting the raw data which is subjected to pre-processing. It results in a HSV (hue, saturation, value) converted image. After pre-processing, the resized format of the data is used to extract the information. In feature extraction the image is segmented and converted into matrix using Gray level co-occurrence matrix algorithm. The further classification is done and result is represented in the form of a decision tree using Support Vector Machine (SVM). The disease that affected the fruit is displayed along with the right fertilizer to be used for the plant.
2020 ◽
Vol 17
(4)
◽
pp. 572-578
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2020 ◽
pp. 095440542095884
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2019 ◽
Vol 27
(06)
◽
pp. 1025-1050
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