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Automated Disease Detection and Classification of Plants Using Image Processing Approaches: A Review

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Proceedings of Second International Conference on Computing, Communications, and Cyber-Security

Part of the book series: Lecture Notes in Networks and Systems ((LNNS,volume 203))

Abstract

For preventing damages in agriculture field plant monitoring is necessary. Plant monitoring or plant disease detection at primary stage can enhance the productivity of crops in terms of quality and quantity both. Field monitoring can be possible in many ways like farmers can take the help of experts or they can use the pesticides also for removing unwanted plants and diseases from plant but experts presence is not possible at every place second problem about pesticides in how much quantity farmers should use it. So these traditional approaches not suitable as much or they takes lots of time. For effective growth of yield and for increment the farmers benefit there is need of automated plant disease detection. Automated plant disease detection can be possible by many techniques such as by Image processing, computer vision, machine learning and through neural network, etc. In this paper, we discussed the Image Processing technique with its approaches such as Image Acquisition, Preprocessing, Segmentation, Feature Extraction and Classification. This paper shows the potential of plant disease detection system that offers the favorable opportunity in agriculture field. The review presents in this paper showing the detailed discussion about existing studies with their strengths and limitation and also giving the information about uncovered research issues on which future scope be there.

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Author information

Authors and Affiliations

  1. G D Goenka University, Gurugram, India

    Shashi & Jaspreet Singh

Authors
  1. Shashi
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  2. Jaspreet Singh
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Editor information

Editors and Affiliations

  1. Department of Computer Science and Engineering, ABES Engineering College, Ghaziabad, India

    Pradeep Kumar Singh

  2. Institute of Computer Science, Polish Academy of Sciences, Warsaw, Poland

    Sławomir T. Wierzchoń

  3. Department of Computer Science and Engineering, Institute of Technology, Nirma University, Ahmedabad, Gujarat, India

    Sudeep Tanwar

  4. Faculty of Mathematics and Information Science, Warsaw University of Technology, Warsaw, Poland

    Maria Ganzha

  5. Instituto de Telecomunicações, Federal University of Piauí (UFPI), Teresina, Piauí, Brazil

    Joel J. P. C. Rodrigues

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Shashi, Singh, J. (2021). Automated Disease Detection and Classification of Plants Using Image Processing Approaches: A Review. In: Singh, P.K., Wierzchoń, S.T., Tanwar, S., Ganzha, M., Rodrigues, J.J.P.C. (eds) Proceedings of Second International Conference on Computing, Communications, and Cyber-Security. Lecture Notes in Networks and Systems, vol 203. Springer, Singapore. https://doi.org/10.1007/978-981-16-0733-2_45

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  • DOI: https://doi.org/10.1007/978-981-16-0733-2_45

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-16-0732-5

  • Online ISBN: 978-981-16-0733-2

  • eBook Packages: EngineeringEngineering (R0)

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