A Novel Methods for Agricultural Plant Leaf Disease Detection
T.Vijaykanth Reddy1, Sashirekhak.K2

1T.Vijaykanth Reddy, Research Scholar, Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Chennai, India.
2Sashirekhak.K, Associate Professor, Saveetha School Of Engineering Saveetha Institute Of Medical And Technical Sciences Chennai, India.

Manuscript received on September 16, 2019. | Revised Manuscript received on 24 September, 2019. | Manuscript published on October 10, 2019. | PP: 2123-2126 | Volume-8 Issue-12, October 2019. | Retrieval Number: L32981081219/2019©BEIESP | DOI: 10.35940/ijitee.L3298.1081219
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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: Horticulture is the primary component of financial development in creating nations. Sickness in crops causes noteworthy decrease in amount and nature of the horticultural item. Manual recognition of the ailments is exceptionally troublesome and not precise for agriculturist. So as to recognize the plant infection at an underlying stage programmed illness recognition methods would be beneficial. Disease discovery involve the steps like Image Acquisition, Image pre-processing, Image Segmentation, Image Feature Extraction, Image classification. This paper talked about the strategy utilized for the recognition of plant ailments utilizing their leaves pictures.
Keywords: k-mean Clustering Segmentation, RGB, Genetic Algorithm, pathogen SVM, KNN.
Scope of the Article: Clustering