[Insight-users] "itkVectorFuzzyConnectednessImageFilter.txx".

[Gabriele Martino]

Hi,

 

id like to know how itk implements scale-based fuzzy connectedness.

Im sorry if my questions are so stupid but im new in image processing and
itk.

 

Ive read this paper, as suggested :

 

" P. K. Saha, J. K. Udupa, and D. Odhner, 

  Scale-based fuzzy connected

 image segmentation: 

  theory, algorithms, and validation, Computer Vision

     

  and Image Understanding 77, 2000, 145-174. "

 

In this paper is presented a particular form of

both homogeneity-feature-based affinity 

and object-feature-based affinity.

 

As for the object component, a filtered value of

a pixel is computed.Ive seen,if im not wrong,

that this component is computed by the method

"computerfilter()" in "itkVectorFuzzyConnectednessImageFilter.txx".

 

As for the homogeneity component, a value,for each couple of pixels,

is calculated based on two digital balls centered on c e d,that is 

the couple of pixels.

But i dont unterstand where scale-based-homogeneity, as presented

in the paper below,is computed in
"itkVectorFuzzyConnectednessImageFilter.txx".

 

Finally i dont unterstand how scale is computed.

Does m_CirclePointsLoc[x][y][z] contain all the pixels that belong to the
digital

ball centered in x,y ?

What does anisotroy_row represent?and anisotropy_col?Why MAXSCALE+5?

 

What is count_obj and count_nonobj?

 

is mean_neighbor a mean of 4-neigh pixels?

 

Cuold you give me a brief description of all that?

 

i hope you'll answer all my questions.

 

Thanks a lot.

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