accurate 3D inspection Marcel Krist, CEO What kind of applications - - PowerPoint PPT Presentation
Photonfocus AG Comparison of 3D Algorithms to ensure accurate 3D inspection Marcel Krist, CEO What kind of applications are using the 3D laser triangulation approach? Different applications need different methods and different 3D hardware and
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Different applications need different methods and different 3D hardware and software
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▪ Dark areas vs. surface defects ▪ Measurements in different planes ▪ Quality control of complex shapes ▪ Volumetric measurements
Source LAP Laser Source Marexi Marine Techn.
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Principle of 3D laser triangulation and accuracy drivers
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Accuracy aspects/drivers ▪ CMOS Sensor (Pixel size, resolution, Noise, etc.) ▪ Top quality lens ▪ Bandpass filter ▪ Speckle-reduced laser ▪ Ideal illumination (LED or Laser in “right” color) ▪ No or very low vibrations on
(“perfect” conveyor belts) ▪ Calibrated system ▪ Set-up of camera and laser ▪ Working distance of camera ▪ Auto exposure ▪ Perfect 3D algorithm
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Pros and Cons of compact or portable 3D scanners using laser triangulation
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CMOS Detector Laser Diode Lens Lens Measurement Range Working distance (stand-off)
Generic compact 3D laser scanner Pros ▪ Fast set-up ▪ Calibrated sensor ▪ Dedicated software ▪ Standard feature set Cons ▪ Fixed angels, reflection and artefacts (disruptions) ▪ Different compact scanners needed for different applications ▪ Space is limited for multisensory systems ▪ Price increases due to complexity ▪ Algorithm changes are almost impossible and algorithm often is unknown
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Typical triangulation setup in a free configruable system
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Camera with one Line Finder Camera with two Line Finders Two cameras to cope with occlusions
Pros of Adaptive configuration ▪ Working distance is variable ▪ Flexible angles of camera/s and laser/s ▪ Variable lens selection ▪ Multiple laser options, fast changes ▪ Algorithm can be adapted to application needs Cons of Adaptive configuration ▪ Deep 3D knowledge required ▪ Components research is needed ▪ Calibration as ongoing task, if set-up change
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Characteristics of specular, Lambertian and Translucid-Lambertian surfaces
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Specular surface (Mirror, …) FOV Cone of light as viewed by the camera
Arrow lengths indicate the power of the reflected light rays in every direction.
These light rays are also visible by the camera!!!
Translucid-Lambertian surface
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Laser stripe on Lambertian and Translucid-Lambertian surfaces
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Intensity profile of the stripe Image 95% of all analysed objects! The maximum intensity is NOT in the middle of the stripe image.
Translucid-Lambertian surface
Intensity profile of the stripe image The maximum intensity is in the middle of the stripe image
Lambertian Surface
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What kind of accuracy can be achieved with the COG method?
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▪ COG = Centre of gravity ▪ Grey values of pixels above threshold ▪ Calculate weighted COG out of grey values of every pixel
Threshold
Le COG = Le + ∑(Pi∙xi)/ ∑(Pi) Left Edge First moment of grey values above threshold Sum of grey values above threshold “Real” resolutions around 1/10
th of a pixel
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What accuracy can be achieved with the Line Finder?
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▪ Digital filtering of noise ▪ Non linear interpolation ▪ Maximum intensity value detector for non-gaussian curves
Resolutions of up to 1/64th of a pixel!!!
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Robustness Analysis of LineFinders in Presence of Reflections with Uncalibrated 3D Profiles
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Generation of Calibrated 3D Profiles with Structured-light 3D Scanners and Tactile Probes
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Comparison of Robustness and Sub-Pixel Resolution with Calibrated 3D Profiles
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Simulations of Sub-Pixel Resolution vs SNR – Gauss Profile with Speckle Noise
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Simulations of Sub-Pixel Resolution vs SNR – Weibull Profile with Speckle Noise
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Mix cameras to complete the 3D
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This area is not visible by camera A Rane Map Camera B Rane Map Camera A Rane Map Camera A and B
Camera A Camera B
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COG delivers 3D scans with rough surfaces – Line Finder has better accuracy
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8x to 10x better detection accuracy
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Photonfocus 3D camera operating modes
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2D only Laser line detection is turned off and the camera behaves as a normal area scan camera. This mode serves as a preview mode in the setup and debugging phase of the vision system. 2D & 3D Laser line detection is turned on. The sensor image (2D image) is transmitted together with the 3D
mode serves as a preview mode in the setup and debugging phase of the triangulation system. 3D only Laser line detection is turned on and only 3D data plus an additional image row for line scan applications is transmitted. The scan rate of this mode is considerably faster than the 2D&3D mode. This is the real working mode of the standard cameras. Moving ROI This feature enables at small ROI’s high frame rates due to the automatic tracking of the laser line.
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Automatic Tracking of Laser Lines in Small ROI‘s
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Benefits of creating your “own” 3D algorithm
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Build your own 3D algorithm and…. ▪ .....you get a flexible, robust and accuract 3D inspection tool ▪ …..you get better detection results and smaller details will be visible ▪ .....you are able to take into consideration your customer feedback and expert knowledge ▪ .....you can improve your line stripe saturation and sub-pixel resolution ▪ .....you know exactly the behaviour of your 3D algorithm and you can control it!
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Photonfocus AG Bahnhofplatz 10 CH-8853 Lachen SZ Switzerland Phone: +41 55 451 00 00 www.photonfocus.com info@photonfocus.com sales@photonfocus.com Date: March 2018 Produced by: Marcel Krist, CEO
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Dark areas vs. surface defects
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Dark areas and holes can be mixed or holes can be not well seen In a depth map, holes can be easily distinguished from the base material Pseudo-color depth image of the wood block Grey image of a wood block
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Volume measurement
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▪ Determination of volumes ▪ Determination of dimensions ▪ Sorting into quality classes
Source: Baixcat Vision S.L. Source Marexi Marine Technology.
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Inspection system for quality control in railway
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Inspection system for quality control
and 2 cameras (1 and 2). [A]: Light-section image from the top camera [1], used to inspect the running surface (triangulation angle of 60° to the laser line generator [3]). [B]: Light-section image from the side- mounted camera [2], used to inspect the rail flank.
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Comparison of COG and Line Finder without noise
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▪ Lambertian surface
COG Line Finder
▪ Translucid-Lambertian surface
COG & Line Finder
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Comparison of COG and Line Finder in the presence of noise
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▪ Lambertian surface ▪ Translucid-Lambertian surface
Line Finder COG COG Line Finder