how to calculate gradient between the currently processed point (x,y) and its neighboring point in one of eight compass direction.
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Dear All,
i'm working for make iterative threshold technique. This technique is first modified with calculating gradient between currently proccessed point (x,y) and its neighboring point in one of eight compass direction that can determined by this equation :
Gd(x,y) = |I(x,y)-I(xd,yd)|
where :
(xd,yd) neighbors to (x,y) in direction d, and I(x,y) and I(xd,yd) denote the gray-level values at locations (x,y) and I(xd,yd). Here d is a value denoting one of eight compass direction.
The value of eight compass direction is
north = [2,10,-6];
north_east = [1,9,-7];
east = [0,8,-8];
south_east = [7,15,-1];
south = [6,14,-2];
south_west = [5,13,-3];
west = [4,12,-4];
nort_west = [3,11,-5];
My problem is how to determined d to take a value of eight compass direction, so i can determined the neighbors point?? i'm really new in gradient based eight direction. Can anyone help me, please?? ^_^
2 Kommentare
Walter Roberson
am 21 Jan. 2012
The first number in each of your triples starts at 0 for east and increases by 1 for each multiple of 45 degrees counter-clockwise from east. But I have no idea what the second and third value in each of your triples are intended to represent or how they are to be used.
Akzeptierte Antwort
Walter Roberson
am 22 Jan. 2012
[nrow, ncol] = size(I);
for x = 1 : ncol
for y = 1 : nrow
if y < nrow; G0(x,y) = abs(I(x,y) - I(x,y+1)); end %E
if x ~= 1 && y < nrow; G1(x,y) = abs(I(x,y) - I(x-1,y+1)); end %NE
if x ~= 1; G2(x,y) = abs(I(x,y) - I(x-1,y)); end %N
[...]
if x < ncol & y < nrow; G8(x,y) = abs(I(x,y) - I(x+1,y+1)); end %SE
end
end
So now what?
2 Kommentare
Walter Roberson
am 22 Jan. 2012
If you do not use those tests then you will get matrix references that are out of range, such as trying to access I(y,0)
Weitere Antworten (2)
Jan
am 22 Jan. 2012
The question is not really clear to me, but I like to guess:
I = rand(100, 100, 3);
m = size(I, 1);
n = size(I, 2);
pre = NaN(size(I));
G_n = pre;
G_s = pre;
G_w = pre;
G_e = pre;
G_nw = pre;
G_sw = pre;
G_ne = pre;
G_se = pre;
G_n(1:m-1, :, :) = diff(I, 1, 1);
G_s(2:m, :, :) = G_n(1:m-1, :, :);
G_e(:, 1:n-1, :) = diff(I, 1, 2);
G_w(:, 2:n, :) = G_e(:, 1:n-1, :);
G_ne(2:m, 1:n-1, :) = I(1:m-1, 2:n, :) - I(2:m, 1:n-1, :);
G_nw(2:m, 2:n, :) = I(1:m-1, 1:n-1, :) - I(2:m, 2:n, :);
G_se(2:m, 1:n-1, :) = I(1:m-1, 2:n, :) - I(2:m, 1:n-1, :);
G_sw(2:m, 2:n, :) = I(1:m-1, 1:n-1, :) - I(2:m, 2:n, :);
Elsya Nurul Aini
am 22 Jan. 2012
11 Kommentare
Jan
am 24 Jan. 2012
What is the current problem exactly?
If you use "G_e = zeros(size(I))" or "G_e = NaN(size(I))" does not matter the ability to be computed. The problem was, that Ge had the size [512 511], and this meand, that you have called "G_e(:, 1:n-1, :) = diff(I, 1, 2);" without the pre-allocation.
The gradient is a vector for 2D data. Building the mean of the components is not meaningful. If the value is +1 in n-s direction and -1 in w-e direction, the mean 0 is free of use.
Walter Roberson
am 24 Jan. 2012
Jan, I think you missed the absolute value bars in the original problem statement.
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