Laser Triangulation Using Spacetime Analysis

There are many different applications where three dimensional data describing the shape of an object is needed. For example it is used in the wood industry to determine the optimal sawing of logs; in the electronics industry to examine solder paste deposits and in the 3D animation industry to import real objects into animated films. Many of those uses have very high requirements of precision.

In this thesis spacetime analysis is applied to laser triangulation in an attempt to eliminate certain artifacts caused mainly by reflectance variations of the surface being measured. It is shown that spacetime analysis do eliminate these artifacts almost completely…


1 Introduction
1.1 Background
1.2 Purpose
1.3 Outline
1.4 Variable Names and Descriptions
2 Basic Theory of Optics
2.1 The Thin Lens Camera Model
2.1.1 The Scheimpflug Condition
2.2 Lens Distortions
2.3 Perspective Distortions
3 Laser Triangulation
3.1 The Camera
3.2 The Laser
3.3 Putting it all Together
3.4 Current Method
3.5 Laser Triangulation Errors
3.5.1 Reflectance Discontinuities
3.5.2 Surface Discontinuities
3.5.3 Occlusion
3.5.4 Laser Speckle
3.5.5 Secondary Reflections
3.5.6 Summary
4 Spacetime Analysis
4.1 Derivation
4.2 The World Sampling Pattern
4.3 The Impact of the Camera and Laser Angles
4.4 Using Relative Coordinates
4.5 Estimating the Spacetime Angle
4.5.1 Scanning a Flat Surface with Reflectance Variations
4.5.2 Using Scatter Data
4.5.3 Using Motion Estimation
4.6 Rolling Shutter
4.7 Choosing the Laser Width
4.8 Spacetime Laser Triangulation Errors
4.8.1 Variations in Surface Properties
4.8.2 Occlusion
4.8.3 Laser Speckle
4.8.4 Secondary Reflections
4.8.5 Summary
5 Algorithm
5.1 Image Acquisition
5.2 Trajectory Extraction
5.3 Peak Detection
5.4 Resampling the Height Data
6 Experiments
6.1 A Box with Braille Printing
6.2 A Sharp Corner
6.3 A Wide Non-Gaussian Intensity Distribution
6.4 Interpolation
6.5 Spacetime Angle Estimation
6.5.1 Minimizing Variance
6.5.2 Using Scatter Data
6.5.3 Motion Estimation
6.6 Increasing Throughput of the Algorithm
6.6.1 Multithreading
6.6.2 GPGPU
7 Conclusions and Future Work
7.1 Conclusions
7.2 Future work

Author: Benderius, Björn

Source: Linköping University

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