How to extract edge from a watersheded image?

[Zetian Yang]

Yeah, this works well!

BTW, the unwanted thicker bounds could be removed by a simple binary
dialation.

Thanks!


On Thu, Mar 28, 2013 at 9:14 PM, Juan Nunez-Iglesias <jni.soma at gmail.com>wrote:

> I think the following should work:
>
> # ws is your watershed label mapfrom scipy import ndimage as nd
> bound = nd.grey_erosion(ws) != nd.grey_dilation(ws)
>
>
> The only bad thing about this is that you'll get slightly thick
> boundaries. I'm not sure if that's a problem for you.
>
>
> On Thu, Mar 28, 2013 at 10:37 AM, Zetian Yang <zetian.yang at gmail.com>wrote:
>
>> Thanks Walt,
>>
>> I need a binary image in which the edges of every labeled region are set
>> to 1.
>> I've found the `find_boundaries` function in the skimage.segmentation
>> module, but its outcome didn't fit my requirement.
>>
>> Currently, I'm using the following algorithm to solve my question.
>>
>> ```
>> bound = np.zeros(data.shape)
>> labels = data.max()
>> for label in labels:
>>      label_data = data==label
>>      bound += label_data - scipy.ndimage.binary_erosion(label_data)
>> ```
>>
>> It seemed work, but I'm not sure its correctness and is there a more
>> efficient method?
>>
>>
>> On Thu, Mar 28, 2013 at 12:00 AM, Stéfan van der Walt <stefan at sun.ac.za>wrote:
>>
>>> Hi Zetian
>>>
>>> On Wed, Mar 27, 2013 at 5:07 AM, Zetian Yang <zetian.yang at gmail.com>
>>> wrote:
>>> > I have been trying the watershed algorithm in the skimage package and
>>> it is
>>> > really fantastic. Recently I have a problem where the edge of one
>>> segmented
>>> > image is need. Is there a convenient way to extract edges of the
>>> watersheded
>>> > result?
>>>
>>> I'm glad you find the package useful!  Do you need the edges as
>>> coordinates, or do you need a bitmap of the edges?  We have marching
>>> squares for contour finding, edge detection, etc.
>>>
>>> Stéfan
>>>
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