Identification of flaws in metallic surfaces using specular and diffuse bispectral light sources

Michael Magee; Steven B. Seida; Ernest A. Franke

doi:10.1117/12.131553

1 November 1992 Identification of flaws in metallic surfaces using specular and diffuse bispectral light sources

Michael Magee, Steven B. Seida, Ernest A. Franke

Proceedings Volume 1825, Intelligent Robots and Computer Vision XI: Algorithms, Techniques, and Active Vision; (1992) https://doi.org/10.1117/12.131553
Event: Applications in Optical Science and Engineering, 1992, Boston, MA, United States

Abstract

A computer vision based automated method for identifying and quantifying flaws in cast metal parts is presented. The specific defects to be isolated consist of small circular concavities in the surface (pits) and larger isolated regions (scratches) that may have been abraded due to cutting or handling operations. The approach taken identifies these anomalous features using two spatially separated light sources with different spectral characteristics to produce highly specular illumination at one wavelength and shallow diffuse illumination at a different wavelength. A bispectral image is processed to yield the sought flaws. This processing consists of identifying regions of interest in the original image that may contain potential flaws and applying a morphological region labelling operation to extract candidate pits and scratches. Geometric constraints are applied to the extracted regions in order to isolate the true flaws. The discussion that follows details the algorithmic approach used to identify flaws as well as characterizing the results obtained.

Citation Download Citation

Michael Magee, Steven B. Seida, and Ernest A. Franke "Identification of flaws in metallic surfaces using specular and diffuse bispectral light sources", Proc. SPIE 1825, Intelligent Robots and Computer Vision XI: Algorithms, Techniques, and Active Vision, (1 November 1992); https://doi.org/10.1117/12.131553

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