re Mean Free Path
the Process\Binary\Distance Map probably provides the answer you want. It generates the distance from each pixel in the foreground to the nearest background pixel - no need to use seed points, the histogram of the distance map catches the whole population.
There are 3D versions in the Image list of plugins.
A more complex question is the average time a randomly moving particle starting in background would take to hit any of the foreground pixels... does anyone have solution other than simulating random movement from randomly selected
________________________________________
From: ImageJ Interest Group [
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[hidden email]]
Sent: 04 April 2015 01:00
To:
[hidden email]
Subject: Mean Free Path and Waterfall or P-Algorithm Segmentation
I'm trying to analyze cytoskeletal filaments and get some quantitative
parameters in terms of density, branching, etc. I'm familiar with existing
techniques like watershed segmentation but even with pre-processing I'm
still having problems with oversegmentation. I've read some research about
refinements of the watershed method, such as Hierarchical segmentation,
waterfall, and p-algorithm segmentation but it seems that even though these
techniques were published some years ago there are no plugins available in
FIJI to do this so firstly is anyone aware of these methods being
implemented in FIJI or other similar packages?
Secondly, I was wondering if anyone is familiar with a plugin for
calculating the "mean free path" in an image. For instance, imagine a binary
image of a spider web, is there a way to randomly place hundreds of seed
points in the image and then calculate a mean free path that they travel
before they run into a white pixel?
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