IMAGE PROCESSING

" Two roads diverged in a wood, and I,
I took the one less traveled by,
And that has made all the difference "-Robert Frost

Identifying Objects based on color (RGB)

Here I  used a bitmap image with different shapes filled with primary colors Red, Blue and Green.

The objects in the image are separated based on the colors. The image is a RGB image which is a 3 dimensional matrix.

Lets use (i,j) for getting the pixel position of the image A.
In the image, A (i, j, 1) represents the value of red color.
A (i, j, 2) represents the green color.
A (i, j, 3) represents the blue color.

To separate the objects of color red:
Check if A (i, j, 1) is positive. [In most cases the value will be 255];
A (i, j, 2) and A (i, j, 3) will be zero.

Similarly, other colors can be separated.

MATLAB CODE:

figure,imshow(A);
title('Original image');

%Preallocate the matrix with the size of A
Red=zeros(size(A));
Blue=zeros(size(A));
Green=zeros(size(A));

for i=1:size(A,1)
for j=1:size(A,2)

%The Objects with Red color
if(A(i,j,1) < = 0)
Red(i,j,1)=A(i,j,1);
Red(i,j,2)=A(i,j,2);
Red(i,j,3)=A(i,j,3);
end

%The Objects with Green color
if(A(i,j,2) < = 0)
Green(i,j,1)=A(i,j,1);
Green(i,j,2)=A(i,j,2);
Green(i,j,3)=A(i,j,3);
end

%The Objects with Blue color
if(A(i,j,3) < = 0)
Blue(i,j,1)=A(i,j,1);
Blue(i,j,2)=A(i,j,2);
Blue(i,j,3)=A(i,j,3);
end

end
end

Red=uint8(Red);
figure,imshow(Red);
title('Red color objects');

Blue=uint8(Blue);
figure,imshow(Blue);
title('Blue color objects');

Green=uint8(Green);
figure,imshow(Green);
title('Green color objects');