Light Stripe Projection (LSP) position improvement by using an adaptive filter based on polynomial and parabola fitting

Samuel H. Chang; Joseph Fuller; Ali Farsaie; Les Elkins

doi:10.1117/12.542220

15 July 2004 Light Stripe Projection (LSP) position improvement by using an adaptive filter based on polynomial and parabola fitting

Samuel H. Chang, Joseph Fuller, Ali Farsaie, Les Elkins

Author Affiliations +

Proceedings Volume 5438, Visual Information Processing XIII; (2004) https://doi.org/10.1117/12.542220
Event: Defense and Security, 2004, Orlando, Florida, United States

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.

Citation Download Citation

Samuel H. Chang, Joseph Fuller, Ali Farsaie, and Les Elkins "Light Stripe Projection (LSP) position improvement by using an adaptive filter based on polynomial and parabola fitting", Proc. SPIE 5438, Visual Information Processing XIII, (15 July 2004); https://doi.org/10.1117/12.542220

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