> On Monday 20 Jun 2016 18:15:30 Dini Nurfiani wrote:
> > Thank you for your explanation. I am a bit confused since you explained
> > about dilation dimension. Are you referring to my first&previous question
> > about dilation macro? Because my recent&new question is about Euclidean
> > Distance Map macro.
>
> I commented on the figures you included in your email.
> The EDM is somewhat equivalent to the nested dilations, but the fractal
> dimension is not computed as the figure seemed to suggest: log of distance
> transform vs log of pixels, but the the way I outlined in my previous
> email.
> It is 1- slope of (log(diameter) vs log(length[diameter]) ).
>
> > But from your explanation about dilation dimension, I tried it as well. I
> > calculated the perimeter (length) first by dividing Area(epsilon)/epsilon
> > and also plotted the log radius vs log perimeter as you mentioned. I
> found
> > the fractal dimension for Koch Snowflake using that method was 1,2283,
> > since the slope is - 0,2283. That value is quite far from the theoretical
> > value, which is 1,2685.
>
> 1. You need to make sure that the largest dilated version of the curve fits
> *completely* within the frame of the image. So the curve has to have lots
> of
> empty space around. In the figure you pasted before, the EDM was truncated
> by
> the image borders. That will underestimate the number of pixels of the
> large
> dilation discs.
>
> 2. Do not use diameters which are too small. At small scales the image you
> used is made of short straight lines (with D=1).
>
> Hope it helps
>
> Gabriel
>
>
>
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