I have quantized hsv into 8×3×3 combinations,so I want to find what is number of pixels per each bin how do I do it

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Answer 1

[Image Analyst]

If you have taken the 3-D histogram, then you have the values. If you really "have quantized hsv into 8×3×3 combinations" then how can you not have that variable??? What happened to it? Did you clear it for some reason? If so, why?

[teja jayavarapu]

Sorry I didn't get you,but any ways I just want to know the way to count no pixels in an image will come under each bin eg:(h==0&s==0&v==0)#this is a bin # then how many such type pixels exists in the image? How do we find that

[Image Analyst]

First give me your code where you converted your rgb image into hsv color space, and the code where you "have quantized hsv into 8×3×3 combinations". And attach the image you are using. Make it easy for me to help you, not hard.

[teja jayavarapu]

a=imread(img); subplot(4,3,2) imshow(img) [rows, cols, numOfBands] = size(a); % totalPixelsOfImage = rows*cols*numOfBands; a = rgb2hsv(a);

% split image into h, s & v planes h = a(:, :, 1); s = a(:, :, 2); v = a(:, :, 3); h=ceil(h*360); c1=find(h>=316&h<=360); h(c1)=1; c2=find(h>=1&h<=25); h(c2)=2; c3=find(h>=26&h<=40); h(c3)=3; c4=find(h>=41&h<=120); h(c4)=4; c5=find(h>=121&h<=190); h(c5)=5; c6=find(h>=191&h<=270); h(c6)=6; c7=find(h>=271&h<=295); h(c7)=7; c8=find(h>=296&h<=315); h(c8)=8; s1=find(s >=0 & s <0.2); s(s1)=1; s2=find(s >=0.2 & s <0.7); s(s2)=2; s3=find(s >=0.7 & s <= 1); s(s3)=3; v1=find(v >=0 & v <0.2); v(v1)=1; v2=find(v >=0.2 & v <0.7); v(v2)=2; v3=find(v >=0.7 & v<=1); v(v3)=3;

[teja jayavarapu]

By the way is there is any way of doing quantification of hsv better

[Image Analyst]

That does not give every combination. That just does one channel at a time. Try this:

clc;    % Clear the command window.
close all;  % Close all figures (except those of imtool.)
workspace;  % Make sure the workspace panel is showing.
format long g;
format compact;
fontSize = 20;

%===============================================================================
% Get the name of the image the user wants to use.
baseFileName = '523.jpg';
folder = fileparts(which(baseFileName)); % Determine where demo folder is (works with all versions).
fullFileName = fullfile(folder, baseFileName);

% Check if file exists.
if ~exist(fullFileName, 'file')
  % The file doesn't exist -- didn't find it there in that folder.
  % Check the entire search path (other folders) for the file by stripping off the folder.
  fullFileNameOnSearchPath = baseFileName; % No path this time.
  if ~exist(fullFileNameOnSearchPath, 'file')
    % Still didn't find it.  Alert user.
    errorMessage = sprintf('Error: %s does not exist in the search path folders.', fullFileName);
    uiwait(warndlg(errorMessage));
    return;
  end
end

%=======================================================================================
% Read in demo image.
rgbImage = imread(fullFileName);
% Get the dimensions of the image.
[rows, columns, numberOfColorChannels] = size(rgbImage);

% Plot 3-D color gamut.
colorcloud(rgbImage);

% Display the original image.
subplot(2, 1, 1);
imshow(rgbImage, []);
axis on;
caption = sprintf('Original Color Image, %s', baseFileName);
title(caption, 'FontSize', fontSize, 'Interpreter', 'None');
hp = impixelinfo(); % Set up status line to see values when you mouse over the image.

% Set up figure properties:
% Enlarge figure to full screen.
set(gcf, 'Units', 'Normalized', 'OuterPosition', [0 0.05 1 0.95]);
% Get rid of tool bar and pulldown menus that are along top of figure.
% set(gcf, 'Toolbar', 'none', 'Menu', 'none');
% Give a name to the title bar.
set(gcf, 'Name', 'Demo by ImageAnalyst', 'NumberTitle', 'Off')

drawnow;

% Convert to hsv color space
hsvImage = rgb2hsv(rgbImage);
% Extract the separate channels
hImage = hsvImage(:, :, 1);
vImage = hsvImage(:, :, 2);
sImage = hsvImage(:, :, 3);
% Create the histogram quantized into 8×3×3 bins
hist3d = zeros(8, 3, 3);
for k = 1 : numel(hImage)
  indexH = floor(8 * hImage(k)) + 1;
  indexS = floor(3 * sImage(k)) + 1;
  indexV = floor(3 * vImage(k)) + 1;
  if indexH > 8
    indexH = 8;
  end
  if indexS > 3
    indexS = 3;
  end
  if indexV > 3
    indexV = 3;
  end
%   fprintf('hImage(%d) = %f, which gives an index of %d.  hImage(%d) = %f, which gives an index of %d.  hImage(%d) = %f, which gives an index of %d.\n',...
%     k, hImage(k), indexH, k2, sImage(k), indexS, k, vImage(k), indexV)
  hist3d(indexH, indexS, indexV) = hist3d(indexH, indexS, indexV) + 1;
end
hist3d % Print to command window.

[teja jayavarapu]

H values should quantize according to the ranges I have mentioned. Does the program given by you will do the same

[teja jayavarapu]

How do I compare this histogram to other images

[Image Analyst]

Look at every element in the two histograms. Not sure exactly what mathematical operation you say when you say "compare". Most likely they WILL be different if they are different images.

[teja jayavarapu]

Why you have taken second dimension as v in the above code

[Image Analyst]

Sorry, it should be h,s,v=1,2,3

hImage = hsvImage(:, :, 1);
sImage = hsvImage(:, :, 2);
vImage = hsvImage(:, :, 3);

Answer 2

[teja jayavarapu]

If I divide image into N×N blocks how do we apply this quantification for different blocks

[Image Analyst]

Same way I already showed you. The code does not care where rgbImage came from: imread() or indexing a block of a larger image. The code works the same regardless of where rgbImage originated.

Answer 3

[teja jayavarapu]

a=imread(img); [rows, cols, numOfBands] = size(a); mr=round(rows/2); mc=round(cols/2); image1=a(1:mr,1:mc); image2=a(1:mr,(mc+1):cols); image3=a((mr+1):rows,1:mc); image4=a((mr+1):rows,(mc+1):cols); subplot(4,3,2) imshow(img) subplot(4,3,5) imshow(image1) subplot(4,3,6) imshow(image2) subplot(4,3,8) imshow(image3) subplot(4,3,9) imshow(image4) I HAVE DIVIDED THE IMAGE INTO 4 BLOCKS IS THERE ANY BETTER WAY OR THERE IS ANY DIRECT COMMAND IN MATLAB TO DO THIS?

[teja jayavarapu]

Sir,please give me some idea about this