DocumentCode :
1504673
Title :
Specular surface inspection using structured highlight and Gaussian images
Author :
Nayar, Shree K. ; Sanderson, Arthur C. ; Weiss, L.E. ; Simon, David A.
Author_Institution :
Robotics Inst., Carnegie-Mellon Univ., Pittsburgh, PA, USA
Volume :
6
Issue :
2
fYear :
1990
fDate :
4/1/1990 12:00:00 AM
Firstpage :
208
Lastpage :
218
Abstract :
The structured highlight inspection method uses an array of point sources to illuminate a specular object surface. The point sources are scanned, and highlights on the object surface resulting from each source are used to derive local surface orientation information. The extended Gaussian image (EGI) is obtained by placing at each point on a Gaussian sphere a mass proportional to the area of elements on the object surface that have a specific orientation. The EGI summarizes shape properties of the object surface and can be efficiently calculated from structured highlight data without surface reconstruction. Features of the estimated EGI including areas, moments, principal axes, homogeneity measures, and polygonality can be used as the basis for classification and inspection. The structured highlight inspection system (SHINY) has been implemented using a hemisphere of 127 point sources. The SHINY system uses a binary coding scheme to make the scanning of point sources efficient. Experiments have used the SHINY system and EGI features for the inspection and classification of surface-mounted-solder joints
Keywords :
computer vision; computerised pattern recognition; encoding; inspection; Gaussian images; SHINY; binary coding; homogeneity; inspection; point sources; polygonality; structured highlight; surface-mounted-solder joints; Area measurement; Cameras; Feature extraction; Image reconstruction; Inspection; Optical reflection; Robots; Shape measurement; Soldering; Surface reconstruction;
fLanguage :
English
Journal_Title :
Robotics and Automation, IEEE Transactions on
Publisher :
ieee
ISSN :
1042-296X
Type :
jour
DOI :
10.1109/70.54736
Filename :
54736
Link To Document :
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