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Potential of ILRIS3D Intensity Data for Planar Surfaces Segmentation.

Chi-Kuei Wang1, Yao-Yu Lu

  • 1Department of Geomatics, National Cheng Kung University, 1 University Road, Tainan 701, Taiwan;

Sensors (Basel, Switzerland)
|February 21, 2012
PubMed
Summary

This study characterizes terrestrial laser scanner intensity data for point cloud segmentation. Grey intensity is preferred, and a 1.5-hour warm-up is recommended for stable data, enabling unique segmentation without calibration.

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Area of Science:

  • Geomatics Engineering
  • Computer Vision
  • Remote Sensing

Background:

  • Terrestrial laser scanner (TLS) intensity values are often unreliable due to hardware and proprietary software limitations.
  • Existing point cloud segmentation methods rarely utilize intensity data, limiting their effectiveness.
  • Characterizing TLS intensity behavior is crucial for developing robust segmentation techniques.

Purpose of the Study:

  • To investigate the stability and characteristics of intensity data from terrestrial laser scanners.
  • To propose a novel point cloud segmentation method leveraging intensity data.
  • To validate the proposed method using data from an ILRIS3D scanner.

Main Methods:

  • Characterization of intensity data (grey and raw formats) from planar surfaces using an ILRIS3D scanner.
Keywords:
ILRIS3DLIDARlaser scanninglidar intensitypoint cloud

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  • Analysis of intensity value variation, patterns, and spatial distribution.
  • Development of a segmentation method based on sequential intensity image analysis.
  • Evaluation of segmentation performance without radiometric calibration.

    • Main Results:

    • Grey intensity format exhibits less variation than raw intensity, making it more suitable for segmentation.
    • A warm-up period of approximately 1.5 hours is suggested for achieving more stable intensity data.
    • The proposed segmentation method effectively segments 3D laser points based on visual cues in intensity image sequences.

    Conclusions:

    • Terrestrial laser scanner intensity data can be reliably used for point cloud segmentation after characterization.
    • The proposed intensity-based segmentation method is unique to ILRIS3D data and bypasses the need for radiometric calibration.
    • Stable intensity data, achieved through characterization and warm-up, enhances the utility of TLS in 3D data processing.