particle tracking
TRANSCRIPT
Simulation secret: How - to
● Run the demo program● Error? Correct it!● Got the exact result● Modify the code● Modify the math● Improved result● Done
Tracking Elongated Particles
● Introduction● Create image with non-overlapping rectangular
particles● Create Ideal Particle● Calculate Least-Squares Fit Function● Extract End Points● Matching End Points
Intro - Background
● The angle of the particle is needed to determine the position of the particle.
● Use least-squares fitting with an elongated ideal particle. ● If we knew the angle of the particle, the entire fitting
process could not be done with a single convolution ● If the angle is unknown, then many fits with ideal particles
at different angles would need to be calculated.● The ends of long particles look more like a circle than any
other part of the particle. ● We can fit with a circle of diameter equal to the minimum
of the length and width of the object. ● This will find the two ends of the particle in one pass
Create image with non-overlapping rectangular particles
20 particles of length L, width W are placed in a NNx X NNy sized image.
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;
Biological Application
IDEA:● Identify regions of the object which look more
like a circle than any other part of the object.● We can fit with a circle at two points on the
object and extract the position and angle