Re: watershed issue

31 Dec 2011


      Thank you Tony,
Modifying the threshold value from 30 to a lower value, gives a
consistent result.

Jean-Patrick
sk.morphology.watershed(bassin_hi,markers,mask=top>30)

On 30 déc, 17:22, Tony Yu  wrote:
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On Fri, Dec 30, 2011 at 8:01 AM, Tony Yu  wrote:
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On Fri, Dec 30, 2011 at 5:39 AM, jip wrote:
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Dear Emmanuelle,
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Sorry for the delay.
I have rewritten a clearer script
https://docs.google.com/open?id=0B-YDFMbEy1grODU1Y2U0OTgtMzk1MS00Mzkx...I
hope.
First, it takes a 12bits imagehttps://docs.google.com/open?id=0B-YDFMbEy1grNWJlYTkwYzYtMjk0ZS00NGVl...(cy3 in the archive), isolates a region andremoves the backgroundhttps://docs.google.com/open?id=0B-YDFMbEy1grNDZjOWZjZjAtMGVmMS00ZTM2...
.
Regional maxima are found to get markers for watershed.
Three kind of maps are also prepared.
Each map, with the markers image, is submitted to the watershed
algorithm.Segmentation is performed with watershed as indicated herehttp://scikits-image.org/docs/dev/auto_examples/plot_watershed.html#e...,
as follow:
segmentation=watershed(map,markers,mask)
map:grayscale image
markers:label image
mask:binary image
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There's a small typo here: watershed should be called as:
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     watershed(map, makers, mask=mask)
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More specifically, in your code, you have:
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    sk.morphology.watershed(bassin_hi,markers,top>30)
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but it should be called as:
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    sk.morphology.watershed(bassin_hi,markers,mask=top>30)
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Without specifying `mask=`, you're setting the connectivity parameter in
watershed. Even with this correction, something seems to be off since
watershed seems to return blank images. Without the masks, it gives what I
would expect. I'm not sure what's going on the masked output.
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-Tony
Actually, I think this masked output is correct: All the markers seem to
land in the masked-out regions.
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mask = top > 30
print np.any(marker * mask)
False
-Tony