CODEWITHSUNDEEP
imagematlabpixel
user2383243
user2383243

Reputation: 33

Matlab - How to measure the dispersion of black in a binary image?

I am comparing RGB images of small colored granules spilled randomly on a white backdrop. My current method involves importing the image into Matlab, converting to a binary image, setting a threshold and forcing all pixels above it to white. Next, I am calculating the percentage of the pixels that are black. In comparing the images to one another, the measurement of % black pixels is great; however, it does not take into account how well the granules are dispersed. Although the % black from two different images may be identical, the images may be far from being alike. For example, assume I have two images to compare. Both show a % black pixels of 15%. In one picture, the black pixels are randomly distributed throughout the image. In the other, a clump of black pixels are in one corner and are very sparse in the rest of the image.

What can I use in Matlab to numerically quantify how "spread out" the black pixels are for the purpose of comparing the two images?

I haven't been able to wrap my brain around this one yet, and need some help. Your thoughts/answers are most appreciated.

Upvotes: 3

Views: 1616

Answers (2)

mlai
mlai

Reputation: 3393

Found an answer to a very similar problem -> https://stats.stackexchange.com/a/13274

Basically, you would use the average distance from a central point to every black pixel as a measure of dispersion.

Upvotes: 1

DasKrümelmonster
DasKrümelmonster

Reputation: 6060

My idea is based upon the mean free path ()used in ideal gad theory / thermodynamics)

First, you must separate your foreground objects, using something like bwconncomp.

The mean free path is calculated by the mean distance between the centers of your regions. So for n regions, you take all n/2*(n-1) pairs, calculate all the distances and average them. If the mean distance is big, your particles are well spread. If it is small, your objects are close together. You may want to multiply the resulting mean by n and divide it by the edge length to get a dimensionless number. (Independent of your image size and independent of the number of particles)

Upvotes: 0

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