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Parametric boundary reconstruction algorithm for industrial CT metrology application.

Zhye Yin1, Kedar Khare, Bruno De Man

  • 1GE Global Research, Niskayuna, NY 12309, USA. yin@research.ge.com

Journal of X-Ray Science and Technology
|August 22, 2009
PubMed
Summary
This summary is machine-generated.

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This study introduces a new algorithm for reconstructing object boundaries from X-ray computed tomography (CT) data, improving dimensional accuracy and efficiency in nondestructive testing and evaluation (NDT/NDE) applications.

Area of Science:

  • Metrology
  • Image Processing
  • Nondestructive Testing and Evaluation (NDT/NDE)

Background:

  • High-energy X-ray computed tomography (CT) systems offer high-resolution imaging for NDT/NDE.
  • Current CT-based metrology relies on pixel-based image analysis and edge detection, which can limit dimensional accuracy due to pixel grid limitations and image artifacts.
  • Coordinate Measuring Machines (CMMs) are the conventional standard for metrology but lack the non-contact, internal imaging capabilities of CT.

Purpose of the Study:

  • To develop a novel algorithm for reconstructing object boundaries directly from CT data.
  • To improve the dimensional accuracy and efficiency of metrology using CT.
  • To enable more direct and accurate representation of object boundaries compared to traditional pixel-based methods.

Main Methods:

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  • A parametric boundary reconstruction algorithm is proposed, focusing on objects with uniform material composition and density.
  • The approach reconstructs boundary parameters directly, reducing algorithmic complexity and eliminating the need for a separate edge detection step.
  • Iterative reconstruction techniques are made more practical through parametric boundary representation.

Main Results:

  • The proposed algorithm significantly reduces computational complexity by reconstructing boundary parameters instead of pixels.
  • Eliminating the edge detection step improves overall dimensional accuracy and reduces processing time.
  • The parametric representation facilitates integration with other metrology modalities like CMMs, allowing prior knowledge incorporation.

Conclusions:

  • The parametric boundary reconstruction algorithm offers a more accurate and efficient method for dimensional metrology using CT.
  • This novel approach overcomes limitations of pixel-based analysis and edge detection artifacts.
  • The method demonstrates feasibility for both simulated and experimental industrial CT data, paving the way for enhanced NDT/NDE applications.