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Kinect-Based Real-Time Acquisition Algorithm of Crop Growth Depth Images

Author

Listed:
  • Shan Hua
  • Minjie Xu
  • Zhifu Xu
  • Hongbao Ye
  • Cheng quan Zhou

Abstract

Kinect 3D sensing real-time acquisition algorithm that can meet the requirements of fast, accurate, and real-time acquisition of image information of crop growth laws has become the trend and necessary means of digital agricultural production management. Based on this, this paper uses Kinect real-time image generation technology to try to monitor and study the depth map of crop growth law in real time, use Kinect to obtain the algorithm of crop growth depth map, and conduct investigation and research. Real-time image acquisition research on crop growth trends provides a basis for in-depth understanding of the application of Kinect real-time image generation technology in research. Kinect image real-time acquisition algorithm is a very important information carrier in agricultural information engineering. The research results show that the real-time Kinect depth image acquisition algorithm can obtain good 3D image data information and can provide valuable data basis for the 3D reconstruction of the later crop growth model, growth status analysis, and real-time monitoring of crop diseases. The data shows that, using Kinect, the real-time feedback speed of crop growth observation can be increased by 45%, the imaging accuracy is improved by 37%, and the related operation steps are simplified by 30%. The survey results show that the crop yield can be increased by about 12%.

Suggested Citation

  • Shan Hua & Minjie Xu & Zhifu Xu & Hongbao Ye & Cheng quan Zhou, 2021. "Kinect-Based Real-Time Acquisition Algorithm of Crop Growth Depth Images," Mathematical Problems in Engineering, Hindawi, vol. 2021, pages 1-9, July.
  • Handle: RePEc:hin:jnlmpe:3913575
    DOI: 10.1155/2021/3913575
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    Cited by:

    1. Jingqian Wen & Yanxin Yin & Yawei Zhang & Zhenglin Pan & Yindong Fan, 2022. "Detection of Wheat Lodging by Binocular Cameras during Harvesting Operation," Agriculture, MDPI, vol. 13(1), pages 1-14, December.
    2. Shuyuan He & Xiuni Li & Menggen Chen & Xiangyao Xu & Fenda Tang & Tao Gong & Mei Xu & Wenyu Yang & Weiguo Liu, 2024. "Crop HTP Technologies: Applications and Prospects," Agriculture, MDPI, vol. 14(5), pages 1-20, May.

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