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Line scale measurement using image registration

Published online by Cambridge University Press:  07 November 2013

P.B. Costa ,
A. Marques ,
F.O. Baldner  and
F.R. Leta
P.B. Costa*
Affiliation:
National Institute of Metrology, Quality and Technology (INMETRO), Av. Nossa Senhora das Graças 50, CEP 25250-020, Duque de Caxias-RJ, Brazil Mechanical Engineering Post-Graduation Program, Universidade Federal Fluminense (UFF), Rua Passo da Patria 156, CEP 24210-240, Niterói-RJ, Brazil
A. Marques
Affiliation:
Mechanical Engineering Post-Graduation Program, Universidade Federal do Paraná (UFPR), Jardim das Américas, CEP 81531-990, Curitiba-PR, Brazil
F.O. Baldner
Affiliation:
National Institute of Metrology, Quality and Technology (INMETRO), Av. Nossa Senhora das Graças 50, CEP 25250-020, Duque de Caxias-RJ, Brazil Mechanical Engineering Post-Graduation Program, Universidade Federal Fluminense (UFF), Rua Passo da Patria 156, CEP 24210-240, Niterói-RJ, Brazil
F.R. Leta
Affiliation:
Mechanical Engineering Post-Graduation Program, Universidade Federal Fluminense (UFF), Rua Passo da Patria 156, CEP 24210-240, Niterói-RJ, Brazil
*
⋆ Correspondence: pbcosta@inmetro.gov.br
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Abstract

Currently, most advances in dimensional metrology might be seen by the evolution of non-contact measurement (optical measurements), in order to provide traceability for different areas that needs to calibrate microscopes or optical measure machines. In a similar way, the use of image processing techniques for the measuring of objects has been the subject of recent studies in computer vision and image metrology. In the attempt to meet the requirements and demands for high accuracy dimensional metrology with image processing techniques, this work will present the application of the image registration technique for the measurement of line scales. In the conventional calibration, the scales are measured in pre-established points, generally in intervals of 10% of the total scale length. With this application, it becomes possible to provide results for all the scale marks quickly and automatically, whereas in the conventional method it would require more time and, thus, a higher cost for the fulfillment of this measurement.

Keywords

Dimensional metrologyline scaleimage processingimage registration
Type
Research Article
Information
International Journal of Metrology and Quality Engineering , Volume 4 , Issue 2 , 2013 , pp. 121 - 125
Copyright
© EDP Sciences 2013

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References

Beers, J.S., Penzes, W.B., The NIST Lenght Scale Interferometer, J. Res. Natl. Inst. Stand. Technol. 104, 225–252 (1999) CrossRefGoogle Scholar
Lassila, A., Ikonen, E., Risk, K., Interferometer for calibration of graduated line scales with a moving CCD camera as a line detector, Appl. Opt. 33, 3600–3603 (1994) CrossRefGoogle Scholar
Eom, T., Han, J., A precision length measuring system for a variety of linear artefacts, Meas. Sci. Technol. 12, 678–701 (2001) CrossRefGoogle Scholar
Deecker, J.E., Steele, A.G., Bosse, H., Douglas, R.J., Analysing redundancy in a line scale comparison using Monte Carlo methods, Meas. Sci. Technol. 19, 064005 (2008) CrossRefGoogle Scholar
Bosse, H., Haessler-Grohne, W., Fluegge, J., Koening, R., Final report on CCL-S3 supplementary line scale comparison Nano 3, Metrologia 40, 04002 (2003) CrossRefGoogle Scholar
B. Zitová, J. Flusser, F. Sroubek, Image Registration: A Survey and Recent Advances, ICIP 2005 Tutorial (Institute of Information Theory and Automation, Czech Republic, 2005)
A.A. Goshtasby, 2-D and 3-D Image Registration for Medical, Remote Sensing and Industrial Applications (Wiley-Interscience, 2005), p. 258
Ferandéz, E., Marti, R., GRASP for seam drawing in mosaicking of aerial photographic maps, J. Heuristics 5, 181–197 (1999) CrossRefGoogle Scholar
Hsieh, J., Fast Stitching algorithm for moving object detection and mosaic construction, Image Vision Computing 22, 291–306 (2004) CrossRefGoogle Scholar
W.K. Pratt, Digital Image Processing (John Wiley, 2007), Vol. 4, p. 782
The Fitness for Purpose of Analytical Methods. A laboratory Guide to Method Validation and Related Topics, 1st edn. (EURACHEM, 1998)