how to make feature vector after edge detection?

A=imread('218.jpg');

% HSV=rgb2hsv(A);% I=uint8(I);
% figure,imshow(HSV);title('Filtered Image');
% 
% imshow(HSV);

HSV=zeros(size(A));
F1=[-1 -1 -1;0 0 0; 1 1 1];
F2=[-1 0 1;-1 0 1; -1 0 1];
A=double(A);
% Gx=[-1+0+1]-[-1+0+1];
% Gy=[-1+0+1]-[-1+0+1];
for i=1:size(A,1)-2
    for j=1:size(A,2)-2
        %Gradient operations
        Gx=sum(sum(F1.*A(i:i+2,j:j+2)));
        Gy=sum(sum(F2.*A(i:i+2,j:j+2)));
        %Magnitude of vector
         HSV(i+1,j+1)=sqrt(Gx.^2+Gy.^2);

      end
  end
  %Define a threshold value
  Thresh=210;
  B=max(HSV,Thresh);
  B(B==round(Thresh))=0;

figure,imshow(B);title('Edge detected Image');

[Guillaume]

I have no idea what it is you're asking but I can tell you that there is a much easier way to calculate your HSV matrix:

F1=[-1 -1 -1;0 0 0; 1 1 1];
F2=[-1 0 1;-1 0 1; -1 0 1];
A=double(A);
HSV = hypot(conv2(A, F1, 'valid'), conv2(A, F2, 'valid'));
%HSV = padarray(HSV, [1 1]);  %if you want the 0 border

No need to implement the convolution yourself.

[MAYA M]

my question is after detecting edge of 10 images. How can we make vector of this edge.

[Image Analyst]

Why? And it's easy to take the coordinates of an edge as a list of (x,y) coordinates if that's what you want using the find() function.