Based on MDS tutorial on his granular material labs page. This slide cover application of particle tracking: on elongated particle and biological application. Please refer to my blog for the basic of particle tracking (in Indonesian language)
2. Simulation secret: How - to
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Run the demo program
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Error? Correct it!
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Got the exact result
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Modify the code
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Modify the math
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Improved result
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Done
4. Intro - Background
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The angle of the particle is needed to determine the
position of the particle.
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Use least-squares fitting with an elongated ideal particle.
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If we knew the angle of the particle, the entire fitting
process could not be done with a single convolution
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If the angle is unknown, then many fits with ideal particles
at different angles would need to be calculated.
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The ends of long particles look more like a circle than any
other part of the particle.
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We can fit with a circle of diameter equal to the minimum
of the length and width of the object.
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This will find the two ends of the particle in one pass
5. Create image with non-overlapping
rectangular particles
20 particles of length L, width W are placed in a
NNx X NNy sized image.
7. Calculate Least-Squares Fit Function
ichi=1./chiimg(im,ip); % The inverse of the least-squares fit function is
% used since it is easier to see peaks than valleys.
simage(ichi); Title('Inverse of Least-Squares Fit Function');
colorbar;
9. Biological Application
IDEA:
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Identify regions of the object which look more
like a circle than any other part of the object.
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We can fit with a circle at two points on the
object and extract the position and angle
27. Result V – Head track, binary
The head track is shown for both the binary
image (blue) and the full image (green). The
binary is shifted by 10 pixels for clarity.
D
O
N
E!!
