Visual Inspection of Machined Metallic High-Precision Surfaces
<p/> <p>This paper presents a surface inspection prototype of an automatic system for precision ground metallic surfaces, in this case bearing rolls. The surface reflectance properties are modeled and verified with optical experiments. The aim being to determine the optical arrangement f...
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2002-01-01
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Series: | EURASIP Journal on Advances in Signal Processing |
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Online Access: | http://dx.doi.org/10.1155/S1110865702203145 |
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doaj-cb71bc0d52864f24aba530c875eb26a62020-11-25T01:00:59ZengSpringerOpenEURASIP Journal on Advances in Signal Processing1687-61721687-61802002-01-0120027650750Visual Inspection of Machined Metallic High-Precision SurfacesPernkopf FranzO'Leary Paul<p/> <p>This paper presents a surface inspection prototype of an automatic system for precision ground metallic surfaces, in this case bearing rolls. The surface reflectance properties are modeled and verified with optical experiments. The aim being to determine the optical arrangement for illumination and observation, where the contrast between errors and intact surface is maximized. A new adaptive threshold selection algorithm for segmentation is presented. Additionally, is included an evaluation of a large number of published sequential search algorithms for selection of the best subset of features for the classification with a comparison of their computational requirements. Finally, the results of classification for 540 flaw images are presented.</p>http://dx.doi.org/10.1155/S1110865702203145visual inspectionsurface reflectionflaw detectionsegmentationstatistical classificationfeature selection |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Pernkopf Franz O'Leary Paul |
spellingShingle |
Pernkopf Franz O'Leary Paul Visual Inspection of Machined Metallic High-Precision Surfaces EURASIP Journal on Advances in Signal Processing visual inspection surface reflection flaw detection segmentation statistical classification feature selection |
author_facet |
Pernkopf Franz O'Leary Paul |
author_sort |
Pernkopf Franz |
title |
Visual Inspection of Machined Metallic High-Precision Surfaces |
title_short |
Visual Inspection of Machined Metallic High-Precision Surfaces |
title_full |
Visual Inspection of Machined Metallic High-Precision Surfaces |
title_fullStr |
Visual Inspection of Machined Metallic High-Precision Surfaces |
title_full_unstemmed |
Visual Inspection of Machined Metallic High-Precision Surfaces |
title_sort |
visual inspection of machined metallic high-precision surfaces |
publisher |
SpringerOpen |
series |
EURASIP Journal on Advances in Signal Processing |
issn |
1687-6172 1687-6180 |
publishDate |
2002-01-01 |
description |
<p/> <p>This paper presents a surface inspection prototype of an automatic system for precision ground metallic surfaces, in this case bearing rolls. The surface reflectance properties are modeled and verified with optical experiments. The aim being to determine the optical arrangement for illumination and observation, where the contrast between errors and intact surface is maximized. A new adaptive threshold selection algorithm for segmentation is presented. Additionally, is included an evaluation of a large number of published sequential search algorithms for selection of the best subset of features for the classification with a comparison of their computational requirements. Finally, the results of classification for 540 flaw images are presented.</p> |
topic |
visual inspection surface reflection flaw detection segmentation statistical classification feature selection |
url |
http://dx.doi.org/10.1155/S1110865702203145 |
work_keys_str_mv |
AT pernkopffranz visualinspectionofmachinedmetallichighprecisionsurfaces AT oaposlearypaul visualinspectionofmachinedmetallichighprecisionsurfaces |
_version_ |
1725211549723787264 |