BWDIST

dt = bwdist(img [,algorithm])

xset('auto clear', 'on');

// First, a simple example to illustrate the concept
A = zeros(15,10);
A(4:12,3:7)=1;
A(4:5,3:4)=0

D = bwdist(A)
D = sqrt(D)
// Note how the values in D were calculated.
// For each pixel p such that A(p)=1, D(p) is the minimum euclidean
// distance of p and the 0-pixels (background).


// -----------------------------------
//  Now to a more interesting example
// -----------------------------------


A = gray_imread(SIPDIR + 'images/escher.png');
imshow(A,2);

D = bwdist(A);       // method=='cuisenaire pmn'
imshow(log(1+D),[]); // normalizes image to enhance visualization

D = bwdist(A,'exact dilations');
imshow(log(1+D),[]);

// To obtain an external EDT, simply invert the shape:
B = 1-A;
D = bwdist(B,'maurer');
imshow(log(1+D),[]);

// To obtain an external+internal EDT, simply compute
// the binary border of the shape and pass its negative
// to bwdist:
A = bwborder(A);
A = 1-A;
D = bwdist(A,'lotufo-zampirolli');
imshow(log(1+D),[]);

// ---------------------------------
//  Other forms to visualize the DT
// ---------------------------------

// Wrapping (note the wavefronts of iso-distance)
imshow(modulo(sqrt(D),10),[])

// Usual:
D = bwdist(A);
D = normal(sqrt(D),1000,1);
imshow(D,hotcolormap(1000));

// There is also of DT application in the example for the "watershed"
// function.

xset('auto clear', 'off');