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A Vision Method for Detecting Citrus Separation Lines Using Line-Structured Light.

Qingcang Yu1, Song Xue1, Yang Zheng1

  • 1School of Computer Science and Technology, Zhejiang Sci-Tech University, Hangzhou 310018, China.

Journal of Imaging
|August 27, 2025
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Summary
This summary is machine-generated.

This study introduces a novel line-structured light method for precise citrus separation line detection. The technique achieves high accuracy, enabling non-destructive, automated citrus processing.

Keywords:
3D reconstructionleast squares fittingline-structured lightprincipal component analysisskeleton extraction

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Area of Science:

  • Computer Vision
  • Agricultural Technology
  • Image Processing

Background:

  • Citrus separation line detection is vital for efficient processing.
  • Existing methods may lack precision or be destructive.
  • Line-structured light technology shows promise in surface analysis.

Purpose of the Study:

  • To develop an automated, non-destructive method for detecting citrus separation lines.
  • To improve the accuracy and reliability of separation line identification in citrus fruits.

Main Methods:

  • Utilized line-structured light technology for citrus surface imaging.
  • Employed a gamma-corrected Otsu method for laser stripe extraction.
  • Applied an improved skeleton extraction algorithm for 3D point cloud generation.
  • Used least squares progressive iterative approximation and principal component analysis for curve fitting and normal derivation.
  • Quantified separation lines using deviation analysis from fitted curves.

Main Results:

  • Achieved an average similarity of 92.5% between detected and manual separation lines.
  • Demonstrated that 95% of detected points had an error of less than 4 pixels.
  • Successfully automated the detection and positioning of citrus separation lines.

Conclusions:

  • The proposed line-structured light method provides high-precision, non-destructive detection of citrus separation lines.
  • This technique meets the stringent requirements for automated citrus splitting processes.
  • Quantitative deviation analysis of geometric features is effective for precise line positioning.