identifyingroundobjects.m

识别飞行的圆形目标

%Identifying Round Objects
%Your goal is to classify objects based on their roundness using
%bwboundaries, a boundary tracing routine. 
%Step 1: Read image 
RGB = imread('pillsetc.png');
imshow(RGB);
%Step 2: Threshold the image
%Convert the image to black and white in order to prepare for boundary tracing 
%using bwboundaries. 
I = rgb2gray(RGB);
threshold = graythresh(I);
bw = im2bw(I,threshold);
figure,imshow(bw)
%Step 3: Remove the noise 
%Using morphology functions, remove pixels which do not belong to the objects of interest.
% remove all object containing fewer than 30 pixels
bw = bwareaopen(bw,30);

% fill a gap in the pen's cap
se = strel('disk',2);
bw = imclose(bw,se);

% fill any holes, so that regionprops can be used to estimate
% the area enclosed by each of the boundaries
bw = imfill(bw,'holes');

figure,imshow(bw)
%Step 4: Find the boundaries 
%Concentrate only on the exterior boundaries. 
%Option 'noholes' will accelerate the processing by preventing bwboundaries
%from searching for inner contours. 
[B,L] = bwboundaries(bw,'noholes');

% Display the label matrix and draw each boundary
figure,imshow(label2rgb(L, @jet, [.5 .5 .5]))
hold on
for k = 1:length(B)
  boundary = B{k};
  plot(boundary(:,2), boundary(:,1), 'w', 'LineWidth', 2)
end
% Step 5: Determine which objects are round
%Estimate each object's area and perimeter.
%Use these results to form a simple metric indicating the roundness of an object:
%metric = 4*pi*area/perimeter^2.This metric is equal to one only for a circle and 
%it is less than one for any other shape. The discrimination process can be controlled 
%by setting an appropriate threshold. In this example use a threshold of 0.94 
%so that only the pills will be classified as round. Use regionprops to obtain
%estimates of the area for all of the objects. Notice that the label matrix returned 
%by bwboundaries can be reused by regionprops. 
stats = regionprops(L,'Area','Centroid');

threshold = 0.94;

% loop over the boundaries
for k = 1:length(B)

  % obtain (X,Y) boundary coordinates corresponding to label 'k'
  boundary = B{k};

  % compute a simple estimate of the object's perimeter
  delta_sq = diff(boundary).^2;    
  perimeter = sum(sqrt(sum(delta_sq,2)));
  
  % obtain the area calculation corresponding to label 'k'
  area = stats(k).Area;
  
  % compute the roundness metric
  metric = 4*pi*area/perimeter^2;
  
  % display the results
  metric_string = sprintf('%2.2f',metric);

  % mark objects above the threshold with a black circle
  if metric > threshold
    centroid = stats(k).Centroid;
    plot(centroid(1),centroid(2),'ko');
  end
  
  text(boundary(1,2)-35,boundary(1,1)+13,metric_string,'Color','y',...
       'FontSize',14,'FontWeight','bold');
  
end

title(['Metrics closer to 1 indicate that ',...
       'the object is approximately round']);