In this report, the authors give a contribution to the study of the influence of inaccuracy of the shape and the position of calibration targets, on the accuracy of Photogrammetry in digitizing micro-features. In a machine vision, camera calibration is performed with planar patterns printed on common papers. When the pattern is small, inaccuracies are experienced. This limitation is overcome by using a coordinate measuring machine to measure the pattern and improve the calibration data. After the calibration improvement, the photogrammetric results are comparable with the existing and more expensive accurate techniques. The use of photogrammetry or computer vision for measuring objects with micro features is a promising research field, yet unexplored. When calibrating cameras for small fields of view is gained, the inaccuracies of the pattern affect the calibration accuracy. A few research papers are available about camera calibration with inaccurate patterns, but no industrial approaches are presented to solve the problem with consequent industrial applications. In the present report, these issues are overcome with a practical method applied to two case studies.

3D image based modelling for inspection of objects with micro-features, using inaccurate calibration patterns: an experimental contribution

PERCOCO, Gianluca;
2017-01-01

Abstract

In this report, the authors give a contribution to the study of the influence of inaccuracy of the shape and the position of calibration targets, on the accuracy of Photogrammetry in digitizing micro-features. In a machine vision, camera calibration is performed with planar patterns printed on common papers. When the pattern is small, inaccuracies are experienced. This limitation is overcome by using a coordinate measuring machine to measure the pattern and improve the calibration data. After the calibration improvement, the photogrammetric results are comparable with the existing and more expensive accurate techniques. The use of photogrammetry or computer vision for measuring objects with micro features is a promising research field, yet unexplored. When calibrating cameras for small fields of view is gained, the inaccuracies of the pattern affect the calibration accuracy. A few research papers are available about camera calibration with inaccurate patterns, but no industrial approaches are presented to solve the problem with consequent industrial applications. In the present report, these issues are overcome with a practical method applied to two case studies.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11589/88192
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