Abstract
Diseases are decreasing the production of the plants. At present, farmers are identifying and diagnosing the diseases and monitoring the health of plants with their own knowledge and experience. Naked eye observation by farmers and experiments on big plantation area can not be possible each time and it can be expensive too. Accurate identification of visually observed diseases, symptoms and controls have not been studied yet. Therefore fast automatic, economical and accurate system is essential to research leaf disease detection of plants. The proposed system is based on image processing, the infected cotton plant leaf image is first segmented using the K-means algorithm. Then Color and texture features have been extracted from the segmented image. Disease detection through feature classification will be done by support vector machine. It could provide significant information about fertilizers, symptoms, prediction, and control of the diseases.
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Singh V, Mishra AK (2017) Detection of plant leaf diseases using image segmentation and soft computing techniques. Elsevier Inform Process Agric 4:41–49
Mr. Dey AK, Meshram MR Image processing based leaf rot diseases, detection of Betal vine, Elsevier. International conference on Computational Modeling and Security (CMS 2016)
Revathi P, Hemalatha M (2014) Cotton leaf spot diseases detection utilizing feature selection with skew divergence method. Int J Scientific Eng Technol (ISSN: 2277-1581) 3(1):22–30
Gulhane VA, Dr Gurjar AA (2011) Detection of diseases on cotton leaves and its possible diagnosis. Int J Image Process (IJIP) 5(5):590–598
Khairnar K, Dagade R (2014) Disease detection and diagnosis on plant using image processing – a review. IJCA (0975-8887) 108(13):36–38
Omrani E et al Potential of radial basis function-based support vector regression for apple disease detection. Measurement 55:512519, Sept-2014, (Elsevier)
Wang H, Li G, Ma Z, Li X Image recognition of plant diseases based on principal component analysis and neural networks, 8th international conference on natural computation (ICNC 2012), pp 246–251, (IEEE)
Arivazhagan S, Newlin Shebiah R, Ananthi S, Vishnu Varthini S (2013) Detection of unhealthy region of plant leaves and classification of plant leaf diseases using texture features. Agric Eng Int: CIGR J 15(1):211–217
Dheeb Al Bashish et. al A framework for detection and classification of plant leaf and stem diseases, 2012 international conference on signal and image processing, pp 113–118, Chennai, India
Phadikar S, Sil J Rice disease identification using pattern recognition techniques. In: Proceedings of 11th International Conference on Computer and Information Technology (ICCIT 2008), 25–27 December, 2008, Khulna, Bangladesh, pp 420–423, (IEEE)
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Khairnar, K., Goje, N. (2020). Image Processing Based Approach for Diseases Detection and Diagnosis on Cotton Plant Leaf. In: Pawar, P., Ronge, B., Balasubramaniam, R., Vibhute, A., Apte, S. (eds) Techno-Societal 2018 . Springer, Cham. https://doi.org/10.1007/978-3-030-16848-3_6
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DOI: https://doi.org/10.1007/978-3-030-16848-3_6
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