<br>Hi Harvey,<br><br>For your convenience, we just added an example on the use of<br>the GrayscaleFunctionDilateImageFilter to:<br><br>Insight/Examples/Filtering/GrayscaleFunctionDilateImageFilter.cxx<br><br>Please also find it attached to this email.<br>
<br><br>The code is quite straight forward:<br><br> * read an image<br> * instantiate filter<br> * create structuring element<br> * connect pipeline : reader, filter, writer<br> * run<br><br><br>Please give it try and let us know if you have any questions.<br>
<br><br> Thanks<br><br><br> Luis<br><br><br><br>---------------------------------------------------------------------------------------<br><div class="gmail_quote">On Tue, Jul 28, 2009 at 6:40 PM, Neal R. Harvey <span dir="ltr"><<a href="mailto:harve@lanl.gov">harve@lanl.gov</a>></span> wrote:<br>
<blockquote class="gmail_quote" style="border-left: 1px solid rgb(204, 204, 204); margin: 0pt 0pt 0pt 0.8ex; padding-left: 1ex;">I am still struggling to implement grayscale morphological operators.<br>
The basic functions have been written:<br>
e.g. <a href="http://www.itk.org/Doxygen310/html/classitk_1_1GrayscaleFunctionDilateImageFilter.html" target="_blank">http://www.itk.org/Doxygen310/html/classitk_1_1GrayscaleFunctionDilateImageFilter.html</a><br>
Unfortunately there are no nice papers or tutorials, or even test code to provide insight as to exactly<br>
how to go about using them.<br>
<br>
It appears that they use a neighborhood kernel and I haven't been able to figure out how to create a<br>
grayscale kernel. I have gone through the book - the part that describes neighborhood iterators, but<br>
so far that hasn't been a great deal of help. The examples they provide don't exactly show how to<br>
assign "grayscale" values to your kernel neighborhood iterator. The examples are for sobel and gaussian<br>
kernels, where there is code in the background that calculates the values for you. You never see the details<br>
of how it is used. The other examples they show in the book are for binary morphology, but that doesn't<br>
require graylevel values kernels, so also isn't much use.<br>
<br>
Basically, I think I need to be able to read in an input image that is to be processed and two images that<br>
define the grayscale structuring element (SE), and output a processed image. One of the SE images<br>
defines the region of support of the SE (i.e. anywhere where the values are greater than 0 are in the<br>
SE's region of support). The other SE image defines the grayscale values in the SE. I then have to use<br>
these two SE images to create a suitable kernel.<br>
<br>
Below is the code that I have written so far, in attempting to write my own Grayscale Morphological<br>
Operator based on the examples provided in the book. As you can see, it's not working and I am not<br>
sure how to solve that problem.<br>
<br>
If anyone has any suggestions or ideas of how to get this working, or where to look to get information<br>
that could lead in that direction, it would be very much appreciated.<br>
<br>
Kindest regards<br>
<br>
Harve<br>
<br>
<br>
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