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Bimodal model-based 3D vision and defect detection for free-form surface inspection

 
: Simler, C.; Berndt, D.; Teutsch, C.

:

Imai, Francisco (Ed.) ; Institute for Systems and Technologies of Information, Control and Communication -INSTICC-, Setubal:
12th International Conference on Computer Vision Theory and Applications, VISIGRAPP 2017. Proceedings. Vol.4: VISAPP : February 27-1, 2017, in Porto, Portugal
SciTePress, 2017
ISBN: 978-989-758-225-7
S.451-458
International Joint Conference on Computer Vision and Computer Graphics Theory and Applications (VISIGRAPP) <12, 2017, Porto>
International Conference on Computer Vision Theory and Applications (VISAPP) <12, 2017, Porto>
Englisch
Konferenzbeitrag
Fraunhofer IFF ()

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.

: http://publica.fraunhofer.de/dokumente/N-502788.html