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Filtering Structured Light Data Detecting the Second Bounce

This paper discusses the challenges of filtering structured light data, particularly distinguishing between primary and secondary reflections. It introduces the JWP Row-Column Filter, designed to reduce noise and improve data clarity during 3D inspection automation. Key topics include the dependence on plane angle, the impact of systematic and discontinuity noise, and the application of the filter in practical scenarios. Results demonstrate significant improvements in measurement accuracy, highlighting the importance of effective filtering in capturing precise reflective data for enhanced automation.

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Filtering Structured Light Data Detecting the Second Bounce

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  1. Filtering Structured Light DataDetecting the Second Bounce Authors: John Palmateer Boeing Commercial Airplane Group Scott Sandwith New River Kinematics 2002 Coordinate Measurement System Committee Providence, RI

  2. Introduction Filtering Structured Light Data • Primary and Secondary Reflections • Noise Reduction Filtering • JWP Row-Column Filter • Plane Angle Dependence • Application: 3D Inspection Automation • Conclusions – Summary

  3. Filter Results Discontinuity noise Measurements confusing primary and secondary reflections Scanner Secondary reflection Data clipped from spheres Filter OFF Filter ON

  4. Primary and Secondary Reflections Camera Secondary laser spots Laser Intersection of camera LOS with secondary reflection Primary laser spots Laser image

  5. Noise Reduction Filtering • Systematic Noise • In-Plane with Laser and Part Edge • Filter Properties • Plane Angle • Array  n x n

  6. JWP Row-Column Filter(1 of 2) Before After

  7. JWP Row-Column Filter

  8. JWP Row-Column Filter(2 of 2) Before After

  9. Plane Angle Dependence 15 degree filter 20 degree filter

  10. Application 3D Inspection Automation

  11. Filtering Structured Light Data

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