International Journal of Progressive Research in Engineering Management and Science
(Peer-Reviewed, Open Access, Fully Referred International Journal)

ISSN:2583-1062 or +91-9098855509
Paper Details


  • Manikandan C ,Manojkumar S ,Haran H


Agriculture productivity is a key factor in economic growth. This is one of the reasons that plant disease detection is crucial in the sector of agriculture, as the presence of illness in plants is extremely common. If necessary precautions are not followed in this region, plants suffer major consequences, which have an impact on the quality, quantity, or productivity of the corresponding products. For instance, the United States has pine trees that are susceptible to a dangerous illness called small leaf disease. The use of an automatic method for plant disease detection is advantageous because it lessens the amount of labour required to monitor large crop farms and can identify disease symptoms at their earliest stage, when they first emerge on plant leaves. The automatic identification and categorization of plant leaf diseases using an image segmentation system is presented in this work. It also includes an overview of various disease categorization strategies that can be applied to the detection of plant leaf disease. Discrete & Convolution technique is used for image segmentation, a crucial step in the disease diagnosis process for plant leaf disease.

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