Mandar, You can use k-means clustering to group pixels of the same class. The scipy module has a clustering function, as well as the PyCluster module.
For the perimeter problem, maybe you can extract the patches as a separate image (without irrelevant pixels) and then use edge detection to get the border pixels. The PIL Image.filter and ImageFilter modules have an FIND_EDGES method. RHH On Fri, Nov 28, 2008 at 1:36 PM, Mandar Sarlashkar <[EMAIL PROTECTED]>wrote: > Hello ! > > Thanks a lot for your reply. > > Analysis is pixel based. > For knowing the land-use mix I can use a 3x3 window operation. > But I dont know how to group pixels of same class (patch) as there will not > be just one patch but several in an image with same pixel values. > For example water - there might be many water bodies dispersed in an > image. > > Also, as you mentioned area calculation is pretty straight but If I am able > to identify patches, how to estimate the number of pixels in an outline for > estimating perimeter. > > Thank you. > > Maddy > > > ------------------------------ > Date: Fri, 28 Nov 2008 12:55:48 -0500 > From: [EMAIL PROTECTED] > To: [EMAIL PROTECTED] > Subject: Re: [Image-SIG] Patch Analysis > > > How are you getting your patches? > If you are doing it on a pixel by pixel basis, then you can simply count > the number of pixels in a patch to estimate the area and you can count the > number of pixels in an outline of the patch to estimate the perimeter. > > 2008/11/28 Mandar Sarlashkar <[EMAIL PROTECTED]> > > > > Dear all, > > I am planning to use PIL in my assignment. > > One of the tasks is to calculate index such as 'Patch Density' for a > classified Land-use Land Cover Image. > > I am not getting how to handle different class patches in an image. > How can I retrieve information for each patch such as area and perimeter? > I can use FRAGSTAS for getting such indices but a python script > or guidance how it can be done using python and PIL will be more helpful. > Thanking you for your time and consideration in advance. > Regards, > Maddy > > ------------------------------ > What's on the ramp today could be on the streets tomorrow. Keep up with > trends on MSN Lifestyle Try it! <http://lifestyle.in.msn.com/> > > _______________________________________________ > Image-SIG maillist - Image-SIG@python.org > http://mail.python.org/mailman/listinfo/image-sig > > > > ------------------------------ > Calling TV buffs! Get TV listings, gossip on your fave stars and updates on > hot new shows Try it now! <http://entertainment.in.msn.com/tv> >
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