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Analysis of Surface Extraction Methods Based on Gradient Operators for Computed Tomography in Metrology Applications
Sinué Ontiveros1, Roberto Jiménez2, José A Yagüe-Fabra3
1Department of Industrial Engineering, Autonomous University of Baja California, 21100 Mexicali, Mexico. sinue.ontiveros@uabc.edu.mx.
Materials (Basel, Switzerland)
|August 22, 2018
Summary
This study presents an adapted 3D Deriche algorithm for surface extraction in Computed Tomography (CT) measurements. The Deriche algorithm significantly reduces deviations on flat surfaces compared to the Canny algorithm, improving measurement accuracy.
Area of Science:
- Metrology
- Image Processing
- Computed Tomography
Background:
- Surface extraction is crucial for accurate Computed Tomography (CT) measurements.
- Traditional methods rely on gray value similarity, but gradient-based approaches offer an alternative.
Purpose of the Study:
- To present and evaluate an adapted 3D Deriche algorithm for surface extraction in CT.
- To compare its performance against an adapted Canny algorithm for various surface types.
Main Methods:
- An adapted 3D Deriche algorithm utilizing gradient information was developed.
- Both the Deriche and Canny algorithms were applied to nine calibrated workpieces with diverse geometries and materials.
- Systematic error and measurement uncertainty were quantified for both methods.
Main Results:
- The Deriche-based algorithm demonstrated a significant reduction in deviations for dimensions defined by flat surfaces.
- Performance was evaluated across different geometries and materials, highlighting the algorithm's robustness.
Conclusions:
- The adapted 3D Deriche algorithm offers improved accuracy for CT metrology, particularly on flat surfaces.
- Gradient-based surface extraction using the Deriche algorithm is a promising approach for enhancing measurement precision.
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