How can i seperate connected objects in binary image?

Question

0 个投票

code:
img = (imread('coins.jpg'));
img_gray = rgb2gray(img);
% Filter image for easier edge detection
m = 12;
n = 12;
img_filter = imfilter(img_gray, fspecial('log',[10 10],1));
%figure, imshow(img_filter), title('f')
% Edge detection
[~, threshold] = edge(img_filter, 'canny');
fudgeFactor = 2;
img_edge = edge(img_filter, 'canny', threshold * fudgeFactor );
figure, imshow(img_edge), title('edge detection')
% Dilate image to make the coin edges complete without holes
se_disk = strel('disk',4);
se_line1 = strel('line',3,100);
se_line2 = strel('line',3,100);
img_dilated = imdilate(img_edge, se_disk);
img_dilated = imdilate(img_dilated, [se_line1 se_line2]);
figure, imshow(img_dilated), title('dilate')
% Remove small objects (noise) and fill complete objects
img_clearborder = imclearborder(img_dilated, 4);
%figure, imshow(BWclear), title('cleared border image');
img_fill = imfill(img_clearborder, 'holes');
figure, imshow(img_fill), title('fill holes')
% Erode image to make a clear cut between objects
se_diamond = strel('diamond',2);
img_erode = imerode(img_fill,se_diamond);
for k=1:3
    img_erode = imerode(img_erode,se_diamond);
end
img_nosmall = bwareaopen(img_erode,300);
figure, imshow(img_nosmall), title('erode')
[B, L] = bwboundaries(img_nosmall);
%ltemp = (L == 1);
se_diamond1 = strel('disk',15);
img_erode1 = imerode(L,se_diamond1);
figure, imshow(label2rgb(img_erode1, @jet, [.5 .5 .5])), title('boundaries')
hold on
stats = regionprops(img_erode1,img(:,:,1),...
    'Area','Centroid','Orientation','EquivDiameter','MeanIntensity');
threshold = 0.8; % For differentiating coins from matches based on an objects circularity
coinCentroids = [];
coinIntensities = [];
matchCentroids = [];
matchAngles = [];
coinRatios = [];
for k = 1:length(B)
    boundary = B{k};
    delta_sq = diff(boundary).^2;
    perimeter = sum(sqrt(sum(delta_sq,2)));
    area = stats(k).Area;
    metric = 4*pi*area/perimeter^2;
    metric_string = sprintf('%2.2f',metric);
    angle_string = sprintf('%2.2f',stats(k).Orientation);
    centroid = stats(k).Centroid;
    if metric > threshold
        % Object is round, therefore a coin
        coinCentroids = [coinCentroids; centroid];
        coinIntensities = [coinIntensities; stats(k).MeanIntensity];
        coinRatios = [coinRatios; stats(k).EquivDiameter/area];
    else
        % Object is a match
        angle = stats(k).Orientation;
        matchCentroids = [matchCentroids; centroid];
        matchAngles = [matchAngles; angle];
    end
      plot(centroid(1),centroid(2),'ko');
end

I attached the input image, the "result image" (it has to be look like this) and the image where i am. My question: How can I separate that 3 objects to 6?