PADDY LEAF DISEASE DETECTION USING SVM CLASSIFIER

Authors

  • S. Pavithra .Electronics & Communication Engineering, VSB Engineering College, Karur.
  • A. Priyadharshini Electronics & Communication Engineering, VSB Engineering College, Karur.
  • V. Praveena Electronics & Communication Engineering, VSB Engineering College, Karur.
  • T. Monika Electronics & Communication Engineering, VSB Engineering College, Karur.

Keywords:

Rice Blast, SVM Classifier, Paddy Blast

Abstract

Disease damage to rice can greatly reduce yield, rice assessing the health condition of rice plant through its leaves .In this paper an automated rice leaf disease detection using image processing techniques is proposed here. An image segmentation and feature extraction technique is used for analysis the disease. Paddy blast and brown spot disease mainly analyzed here. Shape and colour features are extracted using SIFT .After the feature extraction SVM classifier analysis the results. (The overall accuracy of the system should improve for 95.00 percentages).

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Published

2023-05-20

How to Cite

Pavithra, S., Priyadharshini, A., Praveena, V., & Monika, T. (2023). PADDY LEAF DISEASE DETECTION USING SVM CLASSIFIER. International Journal of Communication and Computer Technologies, 3(1), 16–20. Retrieved from https://ijccts.org/index.php/pub/article/view/40

Issue

Section

Research Article