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Proceedings Paper

Light Stripe Projection (LSP) position improvement by using an adaptive filter based on polynomial and parabola fitting
Author(s): Samuel H. Chang; Joseph Fuller; Ali Farsaie; Les Elkins
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Paper Abstract

The problem of using light stripe projection (LSP) for 3D surface reconstruction is addressed in this paper. By using an adaptive filter, we show that we can recover 3D points that normally would go undetected due to light reflection and shape. Further, we show that the filter improves the accuracy of the 3D point coordinates. The filter is based on polynomial and parabola fitting. It generates a bounded polynomial or a smooth parabolic function based on a peak curve from a stripe sample and it adapts the smooth function so that other stripe sample pixels fit a new stripe sample. We then show how the filter is designed to correct the reflection affective pixels of a stripe sample and how it can improve the edge position extracted by any common edge detection method. The effectiveness of the missing 3D point recovery and the 3D point position accuracy improvement is demonstrated by the presentation of experimental results obtained using the methods described in the paper. A test demonstrating the differences between 3D point models generated with and without the adaptive filter is also presented.

Paper Details

Date Published: 15 July 2004
PDF: 8 pages
Proc. SPIE 5438, Visual Information Processing XIII, (15 July 2004); doi: 10.1117/12.542220
Show Author Affiliations
Samuel H. Chang, Spatial Integrated Systems, Inc. (United States)
Joseph Fuller, Spatial Integrated Systems, Inc. (United States)
Ali Farsaie, Spatial Integrated Systems, Inc. (United States)
Les Elkins, Spatial Integrated Systems, Inc. (United States)


Published in SPIE Proceedings Vol. 5438:
Visual Information Processing XIII
Zia-ur Rahman; Robert A. Schowengerdt; Stephen E. Reichenbach, Editor(s)

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