Finite automata model for leaf disease classification

V.T. Krishnaprasath and J Preethi
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V.T. Krishnaprasath: Department of Computer Science and Engineering, Nehru Institute of Engineering and Technology, Anna University, Tamilnadu, India
J Preethi: Department of Computer Science and Engineering, Anna University Regional Campus, Coimbatore, Tamilnadu, India

Agricultural Economics, 2021, vol. 67, issue 6, 220-226

Abstract: In this modern era, the detection of plant disease plays a vital role in the sustainability of agricultural ecosystem. Today, India being second in farming, well-timed information related to crop is still questioning. Indian Government's farmer portal is available for pesticides, fertilisers, and farm machinery. To alleviate this problem, the paper describes a model to validate the leaf image, predicting leaf disease and notifying the farmer in an effective way on the harvest failure to stabilise farming income. For specific consideration on the validation, a data set library with predefined, uniformly scaled, regular image patterns of leaf disease, is maintained. The research suggests that farmers utilising the model can predict the breakout of leaf disease predominantly acquiring 100% yield.

Keywords: agriculture; automata model; image processing; plant disease; segmentation (search for similar items in EconPapers)
Date: 2021
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Persistent link: https://EconPapers.repec.org/RePEc:caa:jnlage:v:67:y:2021:i:6:id:70-2020-agricecon

DOI: 10.17221/70/2020-AGRICECON

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