Posted by
Kyle E. Miller on
Mar 13, 2007; 9:49pm
URL: http://imagej.273.s1.nabble.com/Interparticle-distance-tp3700069p3700074.html
There is a good section in the book Biostatistical Analysis (Zar) to
determine if you have a uniform, clustered, or random distribution of
particles. In brief, divide the area you are examining into a grid that has
the same number of squares as particles. Then count how many participles are
in each square. Then compare the observed distribution with the distribution
predicted by the Poisson distribution. By chance ~36% of the squares should
have no particles, ~36% should have 1 one particles, ~18% should have two
particles and so on. If the distribution is uniform, then there will be
fewer than expected squares with no particles...
Regards,
Kyle
On 3/13/07 4:09 PM, "Karsten Rodenacker" <
[hidden email]> wrote:
> A well-known possibility is for that purpose to calculate the
> distribution of watershed regions area generated from the particles.
> Hence start with a particle binary image, generate the watershed,
> measure the area of the regions. The variation, skewness even
> kurtosis of the area distribution are some sort of measure of disorder.
> Karsten
>
> Am 13.03.2007 um 18:23 schrieb Dan Batzel:
>
>> Thanks for helping me to better frame my question.
>>
>> I am looking to somehow establish the "disorder" of the particles
>> in the
>> image.
>>
>> Their deviation from a grid might be an interesting way to quantify
>> this
>> disorder.
>>
>> -----Original Message-----
>> From: ImageJ Interest Group [mailto:
[hidden email]] On Behalf Of
>> Johannes Schindelin
>> Sent: Tuesday, March 13, 2007 12:47 PM
>> To:
[hidden email]
>> Subject: Re: Interparticle distance
>>
>> Hi,
>>
>> On Tue, 13 Mar 2007, Dan Batzel wrote:
>>
>>> Great program. I am a newbie with a bunch of particles and need to
>>> calculate the average distance between them. There must be a way.
>>
>> First you must decide what you want _exactly_. Do you want the average
>> distance between _neighbouring_ particles? Or do you want to get the
>> next
>> neighbour for each particle, and average _that_ distance? Or do you
>> want
>>
>> to have a measure how much the particle layout deviates from a
>> hexagonal
>>
>> layout?
>>
>> Ciao,
>> Dscho
>
>