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Authors: Christophe Simler ; Dirk Berndt and Christian Teutsch

Affiliation: Fraunhofer Institute for Factory Operation and Automation IFF, Germany

Keyword(s): Detection, Inspection, Free-form Surface, Photogrammetry, Photometric Stereo, Shape Analysis, Model-based, Data Simulation, Merging, Supervised Classification, Image Segmentation.

Related Ontology Subjects/Areas/Topics: Computer Vision, Visualization and Computer Graphics ; Features Extraction ; Image and Video Analysis ; Image Enhancement and Restoration ; Image Formation and Preprocessing ; Segmentation and Grouping

Abstract: This paper presents a 3D vision sensor and its algorithms aiming at automatically detect a large variety of defects in the context of industrial surface inspection of free-form metallic pieces of cars. Photometric stereo (surface normal vectors) and stereo vision (dense 3D point cloud) are combined in order to respectively detect small and large defects. Free-form surfaces introduce natural edges which cannot be discriminated from our defects. In order to handle this problem, a background subtraction via measurement simulation (point cloud and normal vectors) from the CAD model of the object is suggested. This model-based pre-processing consists in subtracting real and simulated data in order to build two complementary “difference” images, one from photometric stereo and one from stereo vision, highlighting respectively small and large defects. These images are processed in parallel by two algorithms, respectively optimized to detect small and large defects and whose results are merged. These algorithms use geometrical information via image segmentation and geometrical filtering in a supervised classification scheme of regions. (More)

CC BY-NC-ND 4.0

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Paper citation in several formats:
Simler, C.; Berndt, D. and Teutsch, C. (2017). Bimodal Model-based 3D Vision and Defect Detection for Free-form Surface Inspection. In Proceedings of the 12th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2017) - Volume 4: VISAPP; ISBN 978-989-758-225-7; ISSN 2184-4321, SciTePress, pages 451-458. DOI: 10.5220/0006113304510458

@conference{visapp17,
author={Christophe Simler. and Dirk Berndt. and Christian Teutsch.},
title={Bimodal Model-based 3D Vision and Defect Detection for Free-form Surface Inspection},
booktitle={Proceedings of the 12th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2017) - Volume 4: VISAPP},
year={2017},
pages={451-458},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006113304510458},
isbn={978-989-758-225-7},
issn={2184-4321},
}

TY - CONF

JO - Proceedings of the 12th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2017) - Volume 4: VISAPP
TI - Bimodal Model-based 3D Vision and Defect Detection for Free-form Surface Inspection
SN - 978-989-758-225-7
IS - 2184-4321
AU - Simler, C.
AU - Berndt, D.
AU - Teutsch, C.
PY - 2017
SP - 451
EP - 458
DO - 10.5220/0006113304510458
PB - SciTePress