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Related Concept Videos

Distance Measurements by Taping01:18

Distance Measurements by Taping

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Tapes are essential in surveying for accurate, durable, and short-distance measurements. Made from lightweight, nylon-coated steel, they offer flexibility and strength for rugged outdoor use. The nylon coating protects against rust and wear, extending the tape's life. Standard lengths, around 30 meters, are marked in meters and millimeters for precision.Surveyors select tapes based on site conditions and accuracy needs. Lightweight, nylon-coated tapes are commonly used for ease of handling and...
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Consider a crane whose telescopic boom rotates with an angular velocity of 0.04 rad/s and angular acceleration of 0.02 rad/s2. Along with the rotation, the boom also extends linearly with a uniform speed of 5 m/s. The extension of the boom is measured at point D, which is measured with respect to the fixed point C on the other end of the boom. For the given instant, the distance between points C and D is 60 meters.
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Related Experiment Video

Updated: Oct 2, 2025

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Vegetable Size Measurement Based on Stereo Camera and Keypoints Detection.

Bowen Zheng1, Guiling Sun1, Zhaonan Meng1

  • 1College of Electronic Information and Optical Engineering, Nankai University, Tianjin 300350, China.

Sensors (Basel, Switzerland)
|February 26, 2022
PubMed
Summary
This summary is machine-generated.

This study introduces a computer vision method for non-contact vegetable measurement in agricultural automation. The system accurately recognizes and estimates the size of cucumbers, eggplants, tomatoes, and peppers using stereo cameras.

Keywords:
computer visionkeypoints detectionstereo cameravegetable size measurement

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Area of Science:

  • Agricultural Automation
  • Computer Vision
  • Robotics

Background:

  • Agricultural automation relies on efficient data acquisition for tasks like harvesting and quality control.
  • Non-contact measurement is crucial for preserving produce integrity and improving operational efficiency.
  • Existing methods often lack the precision or automation required for diverse vegetable types.

Purpose of the Study:

  • To develop an intelligent system for non-contact vegetable recognition and size estimation.
  • To leverage computer vision and stereo camera technology for enhanced agricultural production.
  • To provide a foundation for automated agricultural processes requiring precise vegetable measurements.

Main Methods:

  • Utilized a binocular stereo camera to capture color images and depth maps.
  • Employed object detection networks for classifying four common vegetables: cucumber, eggplant, tomato, and pepper.
  • Implemented keypoint localization and depth data to calculate vegetable dimensions (diameter and length).

Main Results:

  • Achieved accurate classification of four vegetable types within a 60 cm range.
  • Demonstrated precise estimation of vegetable diameter and length using the proposed method.
  • Validated the system's effectiveness for non-contact measurement in an agricultural context.

Conclusions:

  • The developed intelligent method offers an innovative solution for non-contact vegetable measurement.
  • This technology can significantly advance the application of computer vision in agricultural automation.
  • The system provides a reliable tool for improving efficiency and accuracy in farming operations.