extracting contents and calculating area within an image - matlab

Question

Objective :
I need to extract and highlight a specific color from a given image[Say X] and finally I need to calculate the Area of X.
I need help in :
Detecting individual labels in the image[below] in form of a circle.
What I have done :
Below is my code and I have attached the RGB variable's image[below]. I have extracted the "beige color" from the given image(that is X) and labeled it.
To detect the individual component, I tried like the classical "Coins Example [Identifying different coin values from an image using MATLAB", to first detect element. But here as the regions are not uniform, So, I am bit confused.
Code :
clear all; clc;
close all;
I = imread('19.jpg');
%figure;imshow(I);
B = White_Beige(I); // The Function is used to threshold the RGB image
to LAB colorspace. Here, we extract the Beige
color present in the image and provide the final
Black and White image with the presence of Beige
color as Black and rest as white.
%figure; imshow(B);
BW2 = imfill(~B,'holes');
figure; imshow(BW2);
Border = imclearborder(BW2);
[OBL,nbOBObjets] = bwlabel(Border,8);
RGB = label2rgb(OBL,'jet',[0 0 0]);
figure, imshow(RGB);
Any help is much appreciated

Answer 1

maybe this will help:
Note that in this code the "area" occupied by a color is represented as a real number on the interval (0, 1), where 0 means no pixel in the image is that color, and 1 means that all of the pixels in the image are that color.
[A, map] = imread('L8IZU_2.png');
image(A); % display the image
if ~isempty(map)
A = ind2rgb(X, map); % convert image to RGB
end
color_counts = zeros(256, 256, 256);
% color_counts(x, y, z) records the number of pixels in the image
% which have RGB color [x-1, y-1, z-1];
% For example color_counts(1, 1, 1) records the number of pixels in
% the image which have color [0, 0, 0];
% As another example, color_counts(65, 43, 11) records the number of
% pixels in the image which are of color [64, 42, 10];
time_of_last_progress_report = clock;
% traverse the image pixel by pixel
for m = 1:size(A, 1)
for n = 1:size(A, 2)
current_time = clock;
if etime(current_time, time_of_last_progress_report) > 2
percent_progress = 100*(((m - 1)*size(A, 2) + n)/(size(A, 1)*size(A, 2)));
disp(strcat(num2str(percent_progress),'% of the image has been scanned'));
time_of_last_progress_report = clock;
end
current_color = A(m, n, :);
current_color = squeeze(current_color);
% squeeze removes singleton dimensions
% in other words, squeeze converts current_color from a 1x1x3 array into
% a 3x1 array
index = current_color + uint8(ones(size(current_color)));
% Let us say that index = [1, 3, 4];
% We want to increment color_counts(1, 3, 4);
% However, color_counts([1, 3, 4]), or color_counts(index),
% does not return a reference to one single element at that location
% Instead, color_counts([1, 3, 4]) returns a 1x3 vector containing
% the 1st, 3rd, and 4th elements of the color_counts array
% we convert index into a cell array and then convert the cell
% array into a comma separated list.
index2 = num2cell(index);
old_count = color_counts(index2{:});
color_counts(index2{:}) = 1 + old_count;
end
end
disp(' ');% line break
disp('Now sorting colors by how often they apeared....');
color_counts_linear = reshape(color_counts, 1, numel(color_counts));
[color_counts_sorted, indicies] = sort(color_counts_linear, 'descend');
[R,G,B] = ind2sub(size(color_counts),indicies);
R = R - ones(size(R));
G = G - ones(size(G));
B = B - ones(size(B));
areas = (1/(size(A, 1)*size(A, 2))) * color_counts_sorted;
% display the top 5 most common colors
disp(' '); % line break
disp('Top 5 most common colors:');
for k = 1:min(5, numel(areas))
disp(strcat('[', num2str(R(k)), ',', num2str(B(k)), ',', num2str(G(k)),'] : ', num2str(100*areas(k)), '%'));
end