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Banana Pseudostem Width Detection Based on Kinect V2 Depth Sensor.

Jinzhi Wang1,2, Xiuhua Li1, Yonghua Zhou1

  • 1College of Electrical Engineering, Guangxi University, Nanning 530004, China.

Computational Intelligence and Neuroscience
|October 7, 2022
PubMed
Summary

This study presents an automatic method using Kinect V2 sensors for rapid banana pseudostem width measurement. The developed technique achieves high accuracy with minimal error, offering an effective solution for plant stem analysis.

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Area of Science:

  • Agricultural Engineering
  • Computer Vision
  • Plant Science

Background:

  • Accurate measurement of plant stem dimensions is crucial for growth monitoring and yield prediction in agriculture.
  • Traditional methods for measuring banana pseudostem width are often manual, time-consuming, and prone to errors.

Purpose of the Study:

  • To develop and validate an automatic method for measuring banana pseudostem width using a Kinect V2 sensor.
  • To assess the accuracy and efficiency of the proposed measurement technique.

Main Methods:

  • Collected 3D point cloud data of banana pseudostems using a Kinect V2 sensor on a mobile platform.
  • Utilized a cascade classifier for pseudostem recognition and ROI extraction, followed by point cloud processing (down-sampling, noise removal).
  • Segmented the point cloud to calculate horizontal width and corrected it to stem diameter using centerline slope.

Main Results:

  • The automatic measurement method achieved an average measurement error of 2.7 mm.
  • The average relative error was 1.34%, demonstrating high accuracy.
  • The measurement process was rapid, taking approximately 300 ms per measurement.

Conclusions:

  • The developed method provides an effective and efficient solution for automatic banana pseudostem width measurement.
  • This technology can be applied to banana plants and other similar plant species for rapid stem analysis.
  • The study highlights the potential of 3D sensing technology in precision agriculture.