Plant Disease Identification Using SVM and ANN Algorithms
N. Kanaka Durga1, G. Anuradha2
1N. Kanaka Durga, M.Tech Scholar, Department of CSE, Velagapudi Ramakrishna Siddhartha Engineering College, Vijayawada (A.P), India.
2G. Anuradha, Associate Professor, Department of CSE, Velagapudi Ramakrishna Siddhartha Engineering College, Vijayawada (A.P), India.
Manuscript received on 15 February 2019 | Revised Manuscript received on 06 March 2019 | Manuscript Published on 08 June 2019 | PP: 471-473 | Volume-7 Issue-5S4, February 2019 | Retrieval Number: E10990275S419/19©BEIESP
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Tomato and maize are two Indian crops for rural humans to make income. These crops are contaminated with many diseases. Our main goal is to detect the sickness that is infected by the crop and take precautions to protect the crop before it spreads over the complete crop. By doing in this way, there is less loss to the farmers and requires less pesticides and additionally viable to export which no longer have an effect on our monetary growth. In this paper, we use Histogram of Oriented Gradient (HOG) operation and predict features and provide that points to the classification model. At finally, we test the leaves and identify the sickness and shift those records to the farmer through message. Here, take the leaves of the tomato and maize crops and pick out the disease with the aid of using SVM and ANN algorithms in order to find efficient result and accuracy. To predict the illnesses in early stage and take precautions and keep the vegetation leads to extend in production and income.
Keywords: Diseases, SVM, ANN Algorithms, HOG, Vegetation.
Scope of the Article: VLSI Algorithms