Fast and accurate metrology of multi-layered ceramic materials by an automated boundary detection algorithm developed for optical coherence tomography data

Ekberg, Peter; Su, Rong; Chang, Ernest W.; Yun, Seok Hyun; Mattsson, Lars

doi:10.1364/josaa.31.000217

Cited by 9 publications

(11 citation statements)

References 14 publications

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Section: Introductionmentioning

confidence: 72%

“…Besides that, to the best of our knowledge none has so far been presented for industrial applications except for our 2D "ridge detection" method [12]. This paper is a continuation and extension of our previous work in [12]. Here, we present for the first time to our knowledge a simple but accurate and robust 3D image processing method for volumetric OCT data, dedicated to the dimensional metrology of the embedded features in ceramic materials.…”

Section: Introductionmentioning

confidence: 85%

“…It has the advantage of avoiding filtering and preset modeling, and thus introduces a simplification. The algorithm has been described in detail in [12] and its performance has been validated through measuring the thickness of ceramic layers, extracting the boundaries of embedded features with irregular shapes, and detecting geometric deformations. The accuracy and reliability of the algorithm is very high.…”

Section: Ridge Detection Algorithmmentioning

confidence: 99%

“…5(C) is generated after the merging and cleaning process by the assumption of a continuous interface, i.e., the surface in this case. The details of the above processes can be found in the previous publication [12].…”

Section: B Candidate Ridge Detectionmentioning

confidence: 99%

“…We will first review the "ridge detection" for the 2D case [12] and describe in detail the "3D correlation detection" for the 3D volumetric OCT data case. The algorithm performance is finally evaluated thoroughly based on experimental OCT data.…”

Section: Introductionmentioning

confidence: 99%

See 4 more Smart Citations

Accurate and automated image segmentation of 3D optical coherence tomography data suffering from low signal-to-noise levels

Su¹,

Ekberg²,

Leitner³

et al. 2014

J. Opt. Soc. Am. A

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Optical coherence tomography (OCT) has proven to be a useful tool for investigating internal structures in ceramic tapes, and the technique is expected to be important for roll-to-roll manufacturing. However, because of high scattering in ceramic materials, noise and speckles deteriorate the image quality, which makes automated quantitative measurements of internal interfaces difficult. To overcome this difficulty we present in this paper an innovative image analysis approach based on volumetric OCT data. The engine in the analysis is a 3D image processing and analysis algorithm. It is dedicated to boundary segmentation and dimensional measurement in volumetric OCT images, and offers high accuracy, efficiency, robustness, subpixel resolution, and a fully automated operation. The method relies on the correlation property of a physical interface and effectively eliminates pixels caused by noise and speckles. The remaining pixels being stored are the ones confirmed to be related to the target interfaces. Segmentation of tilted and curved internal interfaces separated by ∼10 μm in the Z direction is demonstrated. The algorithm also extracts full-field top-view intensity maps of the target interfaces for high-accuracy measurements in the X and Y directions. The methodology developed here may also be adopted in other similar 3D imaging and measurement technologies, e.g., ultrasound imaging, and for various materials.

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Section: Introductionmentioning

confidence: 72%

Section: Introductionmentioning

confidence: 85%

Section: Ridge Detection Algorithmmentioning

confidence: 99%

Section: B Candidate Ridge Detectionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Accurate and automated image segmentation of 3D optical coherence tomography data suffering from low signal-to-noise levels

Su¹,

Ekberg²,

Leitner³

et al. 2014

J. Opt. Soc. Am. A

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3D precision measurements of meter sized surfaces using low cost illumination and camera techniques

Ekberg

Daemi

Mattsson

2017

Meas. Sci. Technol.

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Using dedicated stereo camera systems and structured light is a well-known method for measuring the 3D shape of large surfaces. However the problem is not trivial when high accuracy, in the range of few tens of microns, is needed. Many error sources need to be handled carefully in order to obtain high quality results. In this study, we present a measurement method based on low-cost camera and illumination solutions combined with high-precision image analysis and a new approach in camera calibration and 3D reconstruction. The setup consists of two ordinary digital cameras and a Gobo projector as a structured light source. A matrix of dots is projected onto the target area. The two cameras capture the images of the projected pattern on the object. The images are processed by advanced subpixel resolution algorithms prior to the application of the 3D reconstruction technique. The strength of the method lays in a different approach for calibration, 3D reconstruction, and high-precision image analysis algorithms. Using a 10 mm pitch pattern of the light dots, the method is capable of reconstructing the 3D shape of surfaces. The precision (1σ repeatability) in the measurements is <10 µm over a volume of 60 × 50 × 10 cm3 at a hardware cost of ~2% of available advanced measurement techniques. The expanded uncertainty (95% confidence level) is estimated to be 83 µm, with the largest uncertainty contribution coming from the absolute length of the metal ruler used as reference.

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TraceableX,Yself-calibration at single nm level of an optical microscope used for coherence scanning interferometry

Ekberg

Mattsson

2018

Meas. Sci. Technol.

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Coherence scanning interferometry used in optical profilers are typically good for Z-calibration at nm-levels, but the X,Y accuracy is often left without further notice than typical resolution limits of the optics, i.e. of the order of ~1 µm. For the calibration of metrology tools we rely on traceable artefacts, e.g. gauge blocks for traditional coordinate measurement machines, and lithographically mask made artefacts for microscope calibrations. In situations where the repeatability and accuracy of the measurement tool is much better than the uncertainty of the traceable artefact, we are bound to specify the uncertainty based on the calibration artefact rather than on the measurement tool. This is a big drawback as the specified uncertainty of a calibrated measurement may shrink the available manufacturing tolerance. To improve the uncertainty in X,Y we can use self-calibration. Then, we do not need to know anything more than that the artefact contains a pattern with some nominal grid. This also gives the opportunity to manufacture the artefact in-house, rather than buying a calibrated and expensive artefact. The self-calibration approach we present here is based on an iteration algorithm, rather than the traditional mathematical inversion, and it leads to much more relaxed constrains on the input measurements. In this paper we show how the X,Y errors, primarily optical distortions, within the field of view (FOV) of an optical coherence scanning interferometry microscope, can be reduced with a large factor. By self-calibration we achieve an X,Y consistency in the 175 × 175 µm2 FOV of ~2.3 nm (1σ) using the 50× objective. Besides the calibrated coordinate X,Y system of the microscope we also receive, as a bonus, the absolute positions of the pattern in the artefact with a combined uncertainty of 6 nm (1σ) by relying on a traceable 1D linear measurement of a twin artefact at NIST.

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Fast and accurate metrology of multi-layered ceramic materials by an automated boundary detection algorithm developed for optical coherence tomography data

Cited by 9 publications

References 14 publications

Accurate and automated image segmentation of 3D optical coherence tomography data suffering from low signal-to-noise levels

Accurate and automated image segmentation of 3D optical coherence tomography data suffering from low signal-to-noise levels

3D precision measurements of meter sized surfaces using low cost illumination and camera techniques

TraceableX,Yself-calibration at single nm level of an optical microscope used for coherence scanning interferometry

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