focus set based reconstruction of micro-objects
TRANSCRIPT
Focus set based reconstruction of micro-objects- http://vision.eng.shu.ac.uk/mechrob04/MechRob-paper.pdf
Focus set based reconstruction of micro-objects
Jan Wedekind
13.9.2004
MiCRoN http://wwwipr.ira.uka.de/~micron/
MMVL http://www.shu.ac.uk/mmvl/
People: Balasundram Amavasai, Manuel Boissenin, Axel Burkle,Fabio Caparrelli, Arul Selvan, Jon Travis
microsystems & machine vision lab - 1 - MiCRoN http://wwwipr.ira.uka.de/~micron/
Focus set based reconstruction of micro-objects- http://vision.eng.shu.ac.uk/mechrob04/MechRob-paper.pdf
micro-vision and micro-robotics
Closed-loop control
• Estimate pose of manipulator in real time
Task planning
• Estimate pose of known micro-objects
• Recognize obstacles for avoiding collisions
• Provide data for determining gripping points
microsystems & machine vision lab - 2 - MiCRoN http://wwwipr.ira.uka.de/~micron/
Focus set based reconstruction of micro-objects- http://vision.eng.shu.ac.uk/mechrob04/MechRob-paper.pdf
present state of micro-vision
characteristics
• Limited depth of focus
• Teleoptical settings
vision problems
• unstable feature extraction
• limited depth of view
⇒ most standard approaches are failing
microsystems & machine vision lab - 3 - MiCRoN http://wwwipr.ira.uka.de/~micron/
Focus set based reconstruction of micro-objects- http://vision.eng.shu.ac.uk/mechrob04/MechRob-paper.pdf
spin images (Andrew Johnson 1997)
microsystems & machine vision lab - 4 - MiCRoN http://wwwipr.ira.uka.de/~micron/
Focus set based reconstruction of micro-objects- http://vision.eng.shu.ac.uk/mechrob04/MechRob-paper.pdf
spin images (Andrew Johnson 1997)
microsystems & machine vision lab - 5 - MiCRoN http://wwwipr.ira.uka.de/~micron/
Focus set based reconstruction of micro-objects- http://vision.eng.shu.ac.uk/mechrob04/MechRob-paper.pdf
depth of focus
• Acquire focus set of images g(x1, x2, z)
• Compute local sharpness measure s(x1, x2, z)
• Compute depth map d(x1, x2) := argmaxz∈Z
(s(x1, x2, z)
)
microsystems & machine vision lab - 6 - MiCRoN http://wwwipr.ira.uka.de/~micron/
Focus set based reconstruction of micro-objects- http://vision.eng.shu.ac.uk/mechrob04/MechRob-paper.pdf
systematic error
test with micro-ridge
• Algorithm fails when contrast low
• Systematic errors
• Trade-off between resolution and stability
⇒ Filter-bench
systematic error
insufficient contrastimage index z
pixel−position in image y
PSF
c
c
ab
d
d
microsystems & machine vision lab - 7 - MiCRoN http://wwwipr.ira.uka.de/~micron/
Focus set based reconstruction of micro-objects- http://vision.eng.shu.ac.uk/mechrob04/MechRob-paper.pdf
multiscale approach
• Recursive filtering
• Not real-time efficient
• Complexity(N = number of pixel)
– O(N) time
– O(N) memory
– 3√
N O(N23 )
parallelisation
• No systematic error(x1,x2)
s
zsmall filter−kernel
s
zmedium−sized filter kernel
s
zlarge filter kernel
image
maximum sharpness
microsystems & machine vision lab - 8 - MiCRoN http://wwwipr.ira.uka.de/~micron/
Focus set based reconstruction of micro-objects- http://vision.eng.shu.ac.uk/mechrob04/MechRob-paper.pdf
results
microsystems & machine vision lab - 9 - MiCRoN http://wwwipr.ira.uka.de/~micron/
Focus set based reconstruction of micro-objects- http://vision.eng.shu.ac.uk/mechrob04/MechRob-paper.pdf
results
microsystems & machine vision lab - 10 - MiCRoN http://wwwipr.ira.uka.de/~micron/
Focus set based reconstruction of micro-objects- http://vision.eng.shu.ac.uk/mechrob04/MechRob-paper.pdf
results
microsystems & machine vision lab - 11 - MiCRoN http://wwwipr.ira.uka.de/~micron/
Focus set based reconstruction of micro-objects- http://vision.eng.shu.ac.uk/mechrob04/MechRob-paper.pdf
results
microsystems & machine vision lab - 12 - MiCRoN http://wwwipr.ira.uka.de/~micron/