matlab - extracting contents and calculating area within an image -
objective :
i need extract , highlight specific color given image[say x] , need calculate area of x.
i need in :
detecting individual labels in image[below] in form of circle.
what have done :
below code , have attached rgb variable's image[below]. have extracted "beige color" given image(that x) , labeled it.
to detect individual component, tried classical "coins example [identifying different coin values image using matlab", first detect element. here regions not uniform, so, bit confused.
code :
clear all; clc; close all; = imread('19.jpg'); %figure;imshow(i); b = white_beige(i); // function used threshold rgb image lab colorspace. here, extract beige color present in image , provide final black , white image presence of beige color black , rest 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 appreciated
maybe help:
note in code "area" occupied color represented real number on interval (0, 1), 0 means no pixel in image color, , 1 means of pixels in image color.
[a, map] = imread('l8izu_2.png'); image(a); % display image if ~isempty(map) = ind2rgb(x, map); % convert image rgb end color_counts = zeros(256, 256, 256); % color_counts(x, y, z) records number of pixels in image % have rgb color [x-1, y-1, z-1]; % example color_counts(1, 1, 1) records number of pixels in % image have color [0, 0, 0]; % example, color_counts(65, 43, 11) records number of % pixels in image of color [64, 42, 10]; time_of_last_progress_report = clock; % traverse image pixel pixel m = 1:size(a, 1) 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 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 1x1x3 array % 3x1 array index = current_color + uint8(ones(size(current_color))); % let index = [1, 3, 4]; % want increment color_counts(1, 3, 4); % however, color_counts([1, 3, 4]), or color_counts(index), % not return reference 1 single element @ location % instead, color_counts([1, 3, 4]) returns 1x3 vector containing % 1st, 3rd, , 4th elements of color_counts array % convert index cell array , convert cell % array 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 how 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 top 5 common colors disp(' '); % line break disp('top 5 common colors:'); k = 1:min(5, numel(areas)) disp(strcat('[', num2str(r(k)), ',', num2str(b(k)), ',', num2str(g(k)),'] : ', num2str(100*areas(k)), '%')); end 
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