how to remove unwanted colors from a Matlab RGB image frame, without using a loop [duplicate] - matlab

Question

This question already has answers here:
How can I convert an RGB image to grayscale but keep one color?
(3 answers)
Closed 6 years ago.
I have an RGB image frame and I want to remove all pixels that are NOT a desired color.
How can do this without a for loop?
% Desired color: R 105, G 112, B 175
% I want to zero all pixels that are not this color (plus a tad).
red_target = 105;
green_target = 112;
blue_target = 175;
tad = 4;
red_low = red_target - tad;
red_hi = red_target + tad;
green_low = green_target - tad;
green_hi = green_target + tad;
blue_low = blue_target - tad;
blue_hi = blue_target + tad;
% Filter out non-target colors:
% Pixel redness is within target; greenness is within target; and blueness within:
% Reset pixel if wrong redness OR wrong greenness OR wrong blueness:
raw_frame_size = size( raw_frame )
rows = raw_frame_size( 1 );
columns = raw_frame_size( 2 );
for row = 1:rows
for column = 1:columns
% Reset RGB pixel value if pixel is outside desired range:
pixel_redness = raw_frame(row,column,1);
pixel_greenness = raw_frame(row,column,2);
pixel_blueness = raw_frame(row,column,3);
if ( ( pixel_redness < red_low ) | ( pixel_redness > red_hi ) ...
| ( pixel_greenness < green_low ) | ( pixel_greenness > green_hi ) ...
| ( pixel_blueness < blue_low ) | ( pixel_blueness > blue_hi ) )
raw_frame( row, column, 1 ) = 0;
raw_frame( row, column, 2 ) = 0;
raw_frame( row, column, 3 ) = 0;
end
end
end

Answer 1

From what I can tell is your objective, this is definitely achievable without for loops using logical indexing.
% Prepare Filter Arrays.
imageSize = size ( raw_frame );
filterArray = zeros ( imageSize ( 1 ) , imageSize ( 2 ) );
% Identify filter pixels.
% This step utilizes logical indexing.
filterArray ( raw_frame(:,:,1) < red_low ) = 1;
filterArray ( raw_frame(:,:,1) > red_high ) = 1;
filterArray ( raw_frame(:,:,2) < green_low ) = 1;
filterArray ( raw_frame(:,:,2) > green_high ) = 1;
filterArray ( raw_frame(:,:,3) < blue_low ) = 1;
filterArray ( raw_frame(:,:,3) > blue_high) = 1;
% Replicate the array to 3D.
filter3d = repmat ( filterArray , [ 1 1 3 ]);
% Filter the image.
% This step also uses logical indexing.
raw_frame ( filter3d ) = 0;
Also, it is a generally bad practice to perform color filtering using an RGB image given the inability to isolate color from saturation and darkness using RGB values alone.
For instance, the RGB values [100,80,40] and [50,40,20] are the same color (hue) but different intensity (lightness or value). A better alternative may be to:
targetRgb(1,1,1) = 105;
targetRgb(1,1,2) = 112;
targetRgb(1,1,3) = 175;
targetHsv = rgb2hsv(targetRgb);
frameHsv = rgb2hsv(raw_frame);
frameSize = size(raw_frame);
hTad = 0.05;
% Values must be in the range [0,1] inclusive.
% Because "hue" is a "colorwheel", -0.3 would be the same value as 0.7.
targetHLow = ( targetHsv(1) - hTad + 1 ) - floor ( targetHsv(1) - hTad + 1);
% A value like 1.3 is the same as 0.3
targetHHigh = ( targetHsv(1) + hTad ) - floor ( targetHsv(1) + hTad );
% Create the filter.
hFilter = zeros(frameSize(1),frameSize(2));
hFilter(hFilter<targetHLow) = 1;
hFilter(hFilter>targetHHigh) = 1;
% Zero out the value channel.
frameV = framHsv(:,:,3);
frameV(hFilter) = 0;
frameHsv(:,:,3) = frameV;
% Convert the modified HSV back to RGB.
frameFiltered = hsv2rgb(frameHsv);

Answer 2

I think there is a much simpler, and computationally efficient implementation. The filter is a 2D logical array.
myrgb = rand(100,100,3);
imagesc(myrgb)
floatNorm = 2^8 - 1;
tad = repmat(4, [100, 100, 3]);
target = repmat([105,112,175], 100*100, 1);
target = reshape(target, [100, 100, 3]);
threshold = (target + tad)/floatNorm;
myFilt = abs(myrgb - 1/2) <= threshold;
myrgb(myFilt) = 0;
imagesc(myrgb)

Answer 3

Can't be done without for loop.
So here is my solution using for loops....
% blue: R 105, G 112, B 175
red_target = 105;
green_target = 112;
blue_target = 175;
tad = 20;
red_low = red_target - tad;
red_hi = red_target + tad;
green_low = green_target - tad;
green_hi = green_target + tad;
blue_low = blue_target - tad;
blue_hi = blue_target + tad;
% Filter out non-target colors:
% Pixel redness is within target; greeness is within target; and blueness within:
% Reset pixel if wrong redness OR wrong greenness OR wrong blueness:
raw_frame_size = size( raw_frame )
rows = raw_frame_size( 1 );
columns = raw_frame_size( 2 );
for row = 1:rows
for column = 1:columns
% Reset RGB pixel value if pixel is outside desired range:
pixel_redness = raw_frame(row,column,1);
pixel_greenness = raw_frame(row,column,2);
pixel_blueness = raw_frame(row,column,3);
if ( ( pixel_redness < red_low ) | ( pixel_redness > red_hi ) ...
| ( pixel_greenness < green_low ) | ( pixel_greenness > green_hi ) ...
| ( pixel_blueness < blue_low ) | ( pixel_blueness > blue_hi ) )
raw_frame( row, column, 1 ) = 0;
raw_frame( row, column, 2 ) = 0;
raw_frame( row, column, 3 ) = 0;
end
end
end