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Implementation of Hybrid Algorithm for the UAV Images Preprocessing Based on Embedded Heterogeneous System: The Case of Precision Agriculture

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Enabling Machine Learning Applications in Data Science

Part of the book series: Algorithms for Intelligent Systems ((AIS))

Abstract

The principle aim of precision farming is to increase the yields of a crop while reducing the consumption of energy and inputs. For this, precision farming operates through the use of new technologies, and the idea is to “produce more with less resources.” The adoption of analysis and decision-making technologies by farmers makes it possible to precisely determine the water, fertilizer, and phytosanitary product needs of crops, that is why it becomes possible to optimize the use of chemical inputs and equipment. These technologies are multiple, such as the Internet of Things which is based on collecting information from sensors but with certain disadvantages, such as limited computing power and limited spaces of crops. But other approaches can solve the problem of precision farming, for instance, artificial intelligence or image processing. In a real case concretization, we discover that an important volume of the database may be lost because of noise and blur of UAV’s camera, and if we correct noised images, we may be more closed to good decisions, that is the reason why this paper will propose a deblurring method of blurred and noised images to improve database content, which will be a proposed additional block to the different algorithms used in precision agriculture. We also propose a hybrid algorithm to eliminate the different noises before processing the algorithms. In our implementation, we used the heterogeneous XU4 system based on a CPU-GPU and the OpenCL parallel programming language. The obtained execution time allowed us to process 50 frames/s.

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Authors and Affiliations

  1. LISTI, ENSA Ibn Zohr University Agadir, 80000, Agadir, Morocco

    Rachid Latif, Laila Jamad & Amine Saddik

Authors
  1. Rachid Latif
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  2. Laila Jamad
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  3. Amine Saddik
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Editor information

Editors and Affiliations

  1. Faculty of Computers and Artificial Intelligence, Cairo University, Giza, Egypt

    Aboul Ella Hassanien

  2. Faculty of Science, Helwan University, Cairo, Egypt

    Ashraf Darwish

  3. Electronics Research Institute, Cairo, Egypt

    Sherine M. Abd El-Kader

  4. College of Science and Humanities, Imam Abdulrahman Bin Faisal University, Jubail, Saudi Arabia

    Dabiah Ahmed Alboaneen

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Latif, R., Jamad, L., Saddik, A. (2021). Implementation of Hybrid Algorithm for the UAV Images Preprocessing Based on Embedded Heterogeneous System: The Case of Precision Agriculture. In: Hassanien, A.E., Darwish, A., Abd El-Kader, S.M., Alboaneen, D.A. (eds) Enabling Machine Learning Applications in Data Science. Algorithms for Intelligent Systems. Springer, Singapore. https://doi.org/10.1007/978-981-33-6129-4_11

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