Re: I need to locate pore clusters

Hi

I have no idea how your data is organized, as a numbers in a 2D-vector or as a binary image?

If it is a binary image you can try to convolve with a disk of radius R, where R is the user specified distance, e.g. 1.5. Afterwards you can do some kind of connected component analysis to find the different clusters.

If it is a 2D-vector you can try to do some algorithm that starts with point no. 1 and mark points close to this. Running through all points you can put the points into the same group if they share a point.

/Allan

vforvasanth wrote:
Hello everyone,

Say there are x number of points on a 2D plane. We need to form
a group using the points which are closer than a specified distance.
The distance will be specified by the user.
Typical timing expectations are 250 ms for 10000 points in LabVIEW .

Examples:
suppose if the distance specified as say 1.5.

Example 1
Consider there are 5 points, which are in the specified location in x,
y plane. The locations are as follows,
Point 1 - 1,s
Point 2 - 2,2
Point 3 - 10,10
Point 4 - 11,11
Point 5 - 100,90

The distance between point 1 & 2 is 1.414, which is less than a user
specified distance of 1.5 in the example. So Point 1 & 2 will form a
group. Similarly 3,4 will form a group. 5 will be alone.

so the result will be a 2D array of,
1,2
3,4
5

Example 2

Point 1 - 1,1
Point 2 - 2,2
Point 3 - 3,3
Point 4 - 11,11
Point 5 - 100,90

Distance = 1.5

Result

1,2,3
4
5

Note - 1,2,3 are formed as a group - Even though 1 & 3 are far than
1.5, but point 2 near to 1 & 3.

I need an algorithm to detect these type of clusters. Can anyone help
me?

.

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