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Detection of Palm Tree Pests Using Thermal Imaging: A Review

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Machine Learning Paradigms: Theory and Application

Part of the book series: Studies in Computational Intelligence ((SCI,volume 801))

Abstract

Due to the extensive stretches of date plantation and topography of traditional grooves in countries such as Saudi Arabia and Egypt, the red palm weevil (RPW) early detection is a significant challenge. The RPW is a palm borer insect that develops within the soft tissues of the trunk and crown, eventually leading to tree death. Early detection of RPW infestation is crucial because, at an early stage of infestation, palms can be treated more efficiently and saved, while the determination of treatment efficacy is hugely vital to optimize palm rescue efforts. Detection is often particularly problematic since not all palms can be accessed and inspected directly. Thermography technique can determine the thermal properties of any objects of interest, and it is a non-destructive. In thermography, the invisible radiation patterns are transformed to visible images called thermal images. Those thermal images are acquired using specific sensors that can be coupled with many available optical systems. Due to the simple operating procedure and the noticeable reductions in equipment cost of thermal imaging systems, it gains popularity in pests’ detection. This chapter discusses the state-of-the-art research concerning the detection methods for detecting infected Palm trees. The study will concentrate on the thermal imaging and its application on red palm weevil detection.

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Author information

Authors and Affiliations

  1. Faculty of Computers and Information, Menoufia University, Menoufia, Egypt

    Ali Ahmed

  2. Faculty of Engineering, Mansoura University, Mansoura, Egypt

    Abdelhameed Ibrahim & Sherif Hussein

  3. D.I.Mendeleyev Institute for Metrology, Saint Petersburg, Russia

    Sherif Hussein

Authors
  1. Ali Ahmed
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  2. Abdelhameed Ibrahim
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  3. Sherif Hussein
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Corresponding author

Correspondence to Abdelhameed Ibrahim .

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Editors and Affiliations

  1. Faculty of Computers and Information, Cairo University, Giza, Egypt

    Aboul Ella Hassanien

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Ahmed, A., Ibrahim, A., Hussein, S. (2019). Detection of Palm Tree Pests Using Thermal Imaging: A Review . In: Hassanien, A. (eds) Machine Learning Paradigms: Theory and Application. Studies in Computational Intelligence, vol 801. Springer, Cham. https://doi.org/10.1007/978-3-030-02357-7_12

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