numpy-discussion

[Numpy-discussion] finding connected areas?

[stephen e. <ste...@gm...>]

I have used adaptive thresholding to turn an image into a binary image
so that I can locate a particularly large bright spot. However, now
that I have the binary image I need to be able to group connected
cell's together and determine their relative sizes. Matlab has a
function called bwlabel (http://tinyurl.com/fcnvd) that labels
connected objects in a matrix. That seems like a good way to start,
and I'm sure there is a way for me to do something similar in numpy,
but how?

Thanks
Stephen Emslie

Re: [Numpy-discussion] finding connected areas?

[Charles R H. <cha...@gm...>]

Stephen,

I don't know of a data structure in numpy or scipy that does this. To do
this myself I use a modified union/find (equivalence relation) algorithm
interfaced to python using boost/python. The same algorithm is also useful
for connecting points on the basis of equivalence relations other than
distance. If there is much interest I could make a standard C version
sometime, but the interface needs some thinking about.

Chuck

On 6/12/06, stephen emslie <ste...@gm...> wrote:
>
> I have used adaptive thresholding to turn an image into a binary image
> so that I can locate a particularly large bright spot. However, now
> that I have the binary image I need to be able to group connected
> cell's together and determine their relative sizes. Matlab has a
> function called bwlabel (http://tinyurl.com/fcnvd) that labels
> connected objects in a matrix. That seems like a good way to start,
> and I'm sure there is a way for me to do something similar in numpy,
> but how?
>
> Thanks
> Stephen Emslie
>
>
> _______________________________________________
> Numpy-discussion mailing list
> Num...@li...
> https://lists.sourceforge.net/lists/listinfo/numpy-discussion
>

Re: [Numpy-discussion] finding connected areas?

[Alexandre F. <ale...@lo...>]

On Tue, Jun 13, 2006 at 01:41:17AM +0100, stephen emslie wrote:
> I have used adaptive thresholding to turn an image into a binary image
> so that I can locate a particularly large bright spot. However, now
> that I have the binary image I need to be able to group connected
> cell's together and determine their relative sizes. Matlab has a
> function called bwlabel (http://tinyurl.com/fcnvd) that labels
> connected objects in a matrix. That seems like a good way to start,
> and I'm sure there is a way for me to do something similar in numpy,
> but how?

You will get this in numarray.nd_image, the function is
called label. It is also available in recent versions of scipy, in
module scipy.ndimage.=20

--=20
Alexandre Fayolle                              LOGILAB, Paris (France)
Formations Python, Zope, Plone, Debian:  http://www.logilab.fr/formations
D=E9veloppement logiciel sur mesure:       http://www.logilab.fr/services
Informatique scientifique:               http://www.logilab.fr/science

Re: [Numpy-discussion] finding connected areas?

[Alexandre F. <ale...@lo...>]

I'm bringing back the discussion on list.=20


On Mon, Jun 19, 2006 at 12:01:27AM +0100, stephen emslie wrote:
> >
> >You will get this in numarray.nd_image, the function is
> >called label. It is also available in recent versions of scipy, in
> >module scipy.ndimage.
>=20
>=20
>=20
> Thanks for pointing me in the right direction. I've been playing around w=
ith
> this and I'm getting along with my problem, which is to find the areas of
> the connected components in the binary image. ndimage.label has been a gr=
eat
> help in identifying and locating each shape in my image, but I am not qui=
te
> sure how to interpret the results. I would like to be able to calculate t=
he
> area of each slice returned by ndimage.labels. Is there a simple way to do
> this?

Yes, you will get an example in
http://stsdas.stsci.edu/numarray/numarray-1.5.html/node98.html
=20
> Also, being very new to scipy I dont fully understand how the slice objec=
ts
> returned by label actually work. Is there some documentation on this modu=
le
> that I could look at?

http://stsdas.stsci.edu/numarray/numarray-1.5.html/module-numarray.ndimage.=
html

--=20
Alexandre Fayolle                              LOGILAB, Paris (France)
Formations Python, Zope, Plone, Debian:  http://www.logilab.fr/formations
D=E9veloppement logiciel sur mesure:       http://www.logilab.fr/services
Informatique scientifique:               http://www.logilab.fr/science