Abstract
This paper presents an image processing algorithm for on-line inspection of large sheet metal car parts. The automatic inspection of stamped sheet metal is not an easy task due to the high reflective nature of the material and the nearly imperceptible characteristics of the defects to be detected. In order to deal with the ubiquitous glints, four images of every zone are acquired illuminating from different directions. The image series is fused using a Haar transform into a single image where the spurious features originated by the glints are eliminated without discarding the salient information. Our results clearly suggest that the proposed fusion scheme offers a powerful way to obtain a clean image where these subtle defects can be detected reliably.
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de la Fuente López, E., Miguel Trespaderne, F. (2009). Inspection of Stamped Sheet Metal Car Parts Using a Multiresolution Image Fusion Technique. In: Fritz, M., Schiele, B., Piater, J.H. (eds) Computer Vision Systems. ICVS 2009. Lecture Notes in Computer Science, vol 5815. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-04667-4_35
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DOI: https://doi.org/10.1007/978-3-642-04667-4_35
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-04666-7
Online ISBN: 978-3-642-04667-4
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