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IMPROVING THE 3D SCAN PRECISION OF LASER
TRIANGULATION
Dr. Athinodoros Klipfel AT – Automation Technology GmbH
THE PRINCIPLE OF LASER TRIANGULATION
X
Y Z
Image of Target Object
Triangulation Geometry Example
Sensor Image of Laser Line
3D LASER TRIANGULATION EXAMPLE OF AN AT 3D CAMERA
Image Acquisition by Means of
High Speed CMOS Sensor Integrated Image Processing
using FPGA technology
Output of Profile Data Over GigE-Vision
ADVANTAGE Profile Frequency up to 72000 Hz!
3D SCAN ACQUISITION
3D Scan
Conveyance of Target Object
- Linear Stage
- Conveyor Belt
- Turntable
Scan Direction
COMMON LINE DETECTION ALGORITHMS
MAX TRSH COG
Reflection of laser light on the object surface causes a Gauss shaped intensity distribution on
sensor image
Finds Position of Maximum Intensity
Finds Threshold Points Finds Center of Gravity
Intensity distribution along a column of the sensor image
PARAMETERS AFFECTING 3D SCAN PRECISION: IMAGE RESOLUTION
Example with AT Camera C5-2040-GigE and α=30°
FoV = 50 mm
dx = 24 µm
dz = 48 µm
dz_COG = 0.75 µm (with Output of 6 Subpixels)
Resolution depends on imaging scale and triangulation angle
Height Resolution: dz=dx/sin(α)
Lateral Resolution: dx=FOV / Pixels per row
COG Height Resolution with 6 Subpixels (factor 26=64): dz_cog=dz/64
PARAMETERS AFFECTING 3D SCAN PRECISION: NOISE DUE TO LASER SPECKLES PHENOMENON
Laser Speckles
The waves of laser light reflected from different parts of the target surface impinge on the sensor
with different phase, which is caused by the different optical path.
The interference of these waves on the sensor causes intensity variations of the laser line image
Laser light reflection impinging on the sensor with different phase
PARAMETERS AFFECTING 3D SCAN PRECISION: NOISE DUE TO LASER SPECKLES PHENOMENON
Typical Sensor Image of 660nm Laser Line. Intensity variations caused by Speckles
Maximum Intensity per Sensor Image Column
Distorted Intensity Distribution along a column due to Speckles
PARAMETERS AFFECTING 3D SCAN PRECISION: NOISE DUE TO LASER SPECKLES PHENOMENON
Example of height profile detected by COG algorithm (laser 660nm)
Standard deviation of noise: ca. 14 µm
3D Setup: AT C5-2040-GigE 2048 Pixels/Profile, FoV=50mm, α=30°, dx=24µm, dz_COG=0.75µm
IMPROVING THE 3D SCAN PRECISION WITH THE FINITE IMPULSE RESPONSE FILTER (FIR)
Smoothing Filter • Numerical Average
• Gauss Average
FIR-Filter (Savitzky-Golay)
Raw intensity data
Smoothed intensity data Selection 5, 7 or 9 Coefficients
COG
Improving the 3D Scan Precision with the Finite Impulse Response Filter (FIR)
Height profile detected by COG algorithm with FIR smoothing filter (Laser 660nm)
Standard deviation of noise: ca. 11 µm
20% improvement
Intensity distribution along a column of sensor image after application of FIR filter in smoothing mode
3D Setup: AT C5-2040-GigE 2048 Pixels/Profile, FoV=50mm, α=30°, dx=24µm, dz_COG=0.75µm
IMPROVING THE 3D SCAN PRECISION WITH THE FIR-PEAK ALGORITHM
Detection of “Zero Crossing” outputs the position of Gauss
curve at a resolution of 6 subpixels (1/64 pixel)
FIR-Filter (Savitzky-Golay)
Raw intensity data
Differential Filter
FIR-PEAK
Selection 5, 7 or 9 Coefficients
IMPROVING THE 3D SCAN PRECISION WITH THE FINITE IMPULSE RESPONSE FILTER (FIR)
Standard deviation of height values in
the profile (µm) Surface Material COG with FIR FIR-PEAK Anodized Aluminum 13 13
Machined Aluminum 10 9 Galvanized Steel 9 9
White Plastic 8 10 Black Plastic 12 12
Comparison between COG with FIR smoothing filter and FIR-PEAK
3D Setup: AT C5-2040-GigE 2048 Pixels/Profile, FoV=50mm, α=30°, dx=24µm, dz_COG=0.75µm
Both algorithms result to almost the same precision.
The COG with FIR filter works better with “thick” lines.
The FIR-PEAK is more precise in applications with “thin” lines.
IMPROVING THE 3D SCAN PRECISION BY MEANS OF LASER WITH SHORTER WAVELENGTH
The Speckle effect depends on the laser wavelength.
Shorter laser wavelength causes less speckles and reduces the noise.
Image of 660nm Laser Line
Image of 405nm Laser Line
IMPROVING THE 3D SCAN PRECISION BY MEANS OF LASER WITH SHORTER WAVELENGTH
3D Setup: AT C5-2040-GigE 2048 Pixels/Profile, FoV=50mm, α=30°, dx=24µm, dz_COG=0.75µm
Height profile of white plastic surface acquired using COG algorithm with FIR smoothing filter
Standard deviation of noise: ca. 6 µm
Laser 405nm
Laser 660nm
Standard deviation of noise: ca.4 µm
30% improvement
IMPROVING THE 3D SCAN PRECISION OF LASER TRIANGULATION
Summary
The 3D scan precision of Laser triangulation depends on:
•Image scaling / resolution
•Laser Speckle effect
The precision can be improved by means of:
• sophisticated algorithms such as the Finite Impulse Response smoothing Filter (FIR) and the FIR-PEAK detection method
•Lasers with shorter wavelength such as 405nm
IMPROVING THE 3D SCAN PRECISION OF LASER TRIANGULATION
Thank you for your attention!
CONTACT INFORMATION
Dr. Athinodoros Klipfel Sales Manager 3D Sensors
AT – Automation Technology GmbH Bad Oldesloe, Germany Tel. +49-4531-88011-0
E-mail: [email protected] Web: http://www.automationtechnology.de/