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High Precision Laser Scanning of Metallic Surfaces
Mid Sweden University, Faculty of Science, Technology and Media, Department of Electronics Design.
Mid Sweden University, Faculty of Science, Technology and Media, Department of Electronics Design.
2017 (English)In: International Journal of Optics, ISSN 1687-9384, E-ISSN 1687-9392, 4134205Article in journal (Refereed) Published
Abstract [en]

Speckle noise, dynamic range of light intensity, and spurious reflections are major challenges when laser scanners are used for 3D surface acquisition. In this work, a series of image processing operations, that is, Spatial Compound Imaging, High Dynamic Range Extension, Gray Level Transformation, and Most Similar Nearest Neighbor are proposed to overcome the challenges coming from the target surface. A prototype scanner for metallic surfaces is designed to explore combinations of these image processing operations. The main goal is to find the combination of operations thatwill lead to the highest possible robustness andmeasurement precision at the lowest possible computational load. Inspection of metallic tools where the surface of its edge must be measured at micrometer precision is our test case. Precision of heights measured without using the proposed image processing is firstly analyzed to be +/- 7.6 mu m at 68% confidence level. The best achieved height precision was +/- 4.2 mu m. This improvement comes at 24 times longer processing time and five times longer scanning time. Dynamic range extension of the image capture improves robustness since the numbers of saturated or underexposed pixels are substantially reduced. Using a high dynamic range (HDR) camera offers a compromise between processing time, robustness, and precision.

Place, publisher, year, edition, pages
2017. 4134205
National Category
Electrical Engineering, Electronic Engineering, Information Engineering
Identifiers
URN: urn:nbn:se:miun:diva-31363DOI: 10.1155/2017/4134205ISI: 000405332500001Scopus ID: 2-s2.0-85024488897OAI: oai:DiVA.org:miun-31363DiVA: diva2:1130524
Available from: 2017-08-10 Created: 2017-08-10 Last updated: 2017-11-29Bibliographically approved

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