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Analysis of Extraction Algorithm for Visual Navigation of Farm Robots Based on Dark Primary Colors

Author

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  • Jin Wang

    (College of Art, Hebei Agricultural University, Baoding, China)

  • Yifei Cui

    (College of Art, Hebei Agricultural University, Baoding, China)

  • Hao Wang

    (College of Art, Hebei Agricultural University, Baoding, China)

  • Mohammad Ikbal

    (Lovely Professional University, Jalandhar, India)

  • Mohammad Usama

    (Sunway University, Malaysia)

Abstract

In order to quickly extract the visual navigation line of farmland robot, an extraction algorithm for dark primary agricultural machinery is proposed. The application of dark primary color principle in new farmland is made clearer by gray scale method, and the soil and crops are obviously separated, and the image processing technology of visual navigation line image of farmland is realized. In binary filtering of gray scale images, the maximum interclass variance method and morphological method are used respectively. The researchers use vertical projection method and least square method to the farmland interval extracted by navigation line. The farmland that needs the guide line image will be accurately located. It is found that the visual navigation extraction algorithm of farmland robot is widely used in the image extraction of navigation lines of various farmland roads and scenes compared with the traditional gray scale algorithm. Image processing has the advantages of clearer image processing.

Suggested Citation

  • Jin Wang & Yifei Cui & Hao Wang & Mohammad Ikbal & Mohammad Usama, 2021. "Analysis of Extraction Algorithm for Visual Navigation of Farm Robots Based on Dark Primary Colors," International Journal of Agricultural and Environmental Information Systems (IJAEIS), IGI Global, vol. 12(2), pages 61-72, April.
    • Handle: RePEc:igg:jaeis0:v:12:y:2021:i:2:p:61-72
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