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Accurate and automated image segmentation of 3D optical coherence tomography data suffering from low signal to noise levels
KTH, School of Industrial Engineering and Management (ITM), Production Engineering, Metrology and Optics. (Industrial Metrology and Optics)ORCID iD: 0000-0003-0776-3716
KTH, School of Industrial Engineering and Management (ITM), Production Engineering, Metrology and Optics.
KTH, School of Industrial Engineering and Management (ITM), Production Engineering, Metrology and Optics.ORCID iD: 0000-0002-0105-4102
(English)In: IEEE Transactions on Image Processing, ISSN 1057-7149, E-ISSN 1941-0042Article in journal, News item (Other academic) Submitted
Abstract [en]

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 a new image analysis approach based on volumetric OCT data. The engine in the analysis is a 3D image processing and analysis algorithm. It is dedicated for boundary segmentation and dimensional measurement in volumetric OCT images, and offers high accuracy, efficiency, robustness, sub-pixel resolution and a fully automated operation. The method relies on the correlation property of a physical interface and eliminates effectively 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 z-direction is demonstrated. The algorithm also extracts full-field top-view intensity maps of the target interfaces for high-accuracy measurements in 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.

Keyword [en]
3D image processing, Automatic optical inspection, Ceramics, Correlation, Image segmentation, Metrology, Noise reduction, Sub-pixel resolution, Tomography
National Category
Engineering and Technology
Research subject
SRA - Production
Identifiers
URN: urn:nbn:se:kth:diva-144594OAI: oai:DiVA.org:kth-144594DiVA: diva2:714262
Projects
Multilayer (FP7-NMP4-2007-214122)
Funder
XPRES - Initiative for excellence in production researchEU, FP7, Seventh Framework Programme, FP7-NMP4-2007-214122
Note

QS 2014

Available from: 2014-04-25 Created: 2014-04-25 Last updated: 2017-12-05Bibliographically approved

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Su, Rong

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