Paddy Blast Detection using SVM Machine Classifier

  • P. Jona Innisai Rani, Dr. M. P. Kavitha


Location of plant malady may require gigantic sum of information and work on plant infection. Hence, we utilize the picture handling method for discovery of plant’s leaf discovery. The proposed framework points to overcome the pitfalls of the existing framework and gives highlights such as location of plant illness, feature extraction, investigation of information. This is possible by using the proposed SVMmachine classifier. So in this investigate the most objective is to develop a model framework for recognizing the paddy malady, which is Paddy blast. The technique includes collection of samples, pre-processing, extraction and classification. cture collection, picture preparing, include extraction and classification.. In testing stage, all paddy tests are passed through the leaf color analysis to identify the typical paddy leaf picture. The efficiency of the system is evaluated in terms of specificity, accuracy and MSE.

How to Cite
P. Jona Innisai Rani, Dr. M. P. Kavitha. (2022). Paddy Blast Detection using SVM Machine Classifier. Design Engineering, (1), 3181 - 3190. Retrieved from