Posted by
Aloysius Phillips on
May 24, 2007; 8:34pm
URL: http://imagej.273.s1.nabble.com/particle-distribution-randomness-uniformity-tp3699301p3699311.html
Kiran,
The open source stat package R has plugins called "splancs" and "spatstat".
These will tell you whether your data points are self-avoiding, clustered or
distributed in a poisson fashion. A google search for "point pattern
analysis" will be helpful towards how these statistical methods operate. I
have a similar dataset but havent gotten as far as the nuts and bolts of
these programs. The programs can input the image but its probably easier to
export the (x,y) coordinates from imageJ and import the matrix. Thats as far
as I've gotten. Good luck.
Aloysius Phillips
Division of Invertebrates
American Museum of Natural History
79th street and Central Park West
10024
Voice (212) 769-5410
FAX (212) 769-5277
----- Original Message -----
From: "Anast, John" <
[hidden email]>
To: <
[hidden email]>
Sent: Thursday, May 24, 2007 1:50 PM
Subject: Re: particle distribution - randomness/uniformity
> Kiran,
>
> Have you looked at the std dev of the shortest distances...should have a
> very low stdev for uniform distribution. With clusters, you may want to
> look at three or N- nearest neighbors for each particle.
>
> Another approach is to grid the image and count particles in each box
> and look at that distribution vs box size
>
> ...john
>
> -----Original Message-----
> From: ImageJ Interest Group [mailto:
[hidden email]] On Behalf Of
> Annapragada, Sriram K.
> Sent: Thursday, May 24, 2007 12:30 PM
> To:
[hidden email]
> Subject: particle distribution - randomness/uniformity
>
> I had the following question. Any help will be really appreciated
>
> I have a stack of binary-8bit images with a random distribution of
> particles; also each image has a different number of particles. I was
> trying to find out how random the distribution was i.e. how uniformly
> the particles are distributed across each image.
>
> One of the previous mails to this list suggested averaging the shortest
> distance between all the particles - but that does not show any
> significant difference between images.
>
> Is there a another way to do this?
>
> thanks,
> Kiran.
>