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 Comments
Walter Roberson
on 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.
Elsya Nurul Aini
on 22 Jan 2012
Accepted Answer
More Answers (2)
Jan
on 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, :);
1 Comment
Elsya Nurul Aini
on 22 Jan 2012
Elsya Nurul Aini
on 22 Jan 2012
11 Comments
Walter Roberson
on 22 Jan 2012
What are the size() of each of the array? If one of them is not the same size as the others, which one is it? Now go back to the code and figure out why that one is smaller.
Elsya Nurul Aini
on 23 Jan 2012
Jan
on 23 Jan 2012
Did you use my code, but forget to include the "G_[] = pre;" lines? Then add these lines.
Walter Roberson
on 23 Jan 2012
If you are in the south-most row, what is south of it that you could calculate a "south" value for that row?
Jan
on 23 Jan 2012
Did you use my code, but forget to include the "G_[] = pre;" lines? Then add these lines.
Using the mean of these values is unusual: The gradient in n-s and e-w direction have a shorter base line, while the gradients in ne-sw and nw-se direction use a base line, which is sqrt(2) times longer.
Elsya Nurul Aini
on 24 Jan 2012
Walter Roberson
on 24 Jan 2012
Is it meaningful to be using those zeros that are not being replaced by calculated values?
Elsya Nurul Aini
on 24 Jan 2012
Walter Roberson
on 24 Jan 2012
You could apply your functions to your G_* arrays indexed at (2:end-1, 2:end-1) . You at least have calculated data for all those locations. But Jan or I cannot offer corrected code as it does not make sense to us to be taking the mean or whatever of those values; see Jan's comments about the differing scales.
Jan
on 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
on 24 Jan 2012
Jan, I think you missed the absolute value bars in the original problem statement.
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