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Identifying Round Objects

This example shows how to classify objects based on their roundness using bwboundaries, a boundary tracing routine.

Step 1: Read an Image

Read in pills_etc.png.

RGB = imread("pillsetc.png");
imshow(RGB)

Figure contains an axes object. The axes object contains an object of type image.

Step 2: Threshold the Image

Convert the image to black and white in order to prepare for boundary tracing using bwboundaries.

I = im2gray(RGB);
bw = imbinarize(I);
imshow(bw)

Figure contains an axes object. The axes object contains an object of type image.

Step 3: Preprocess the Image

Using morphology functions, remove pixels which do not belong to the objects of interest.

Remove all objects containing fewer than 30 pixels.

minSize = 30;
bw = bwareaopen(bw,minSize);
imshow(bw)

Figure contains an axes object. The axes object contains an object of type image.

Fill a gap in the pen's cap.

se = strel("disk",2);
bw = imclose(bw,se);
imshow(bw)

Figure contains an axes object. The axes object contains an object of type image.

Fill any holes, so that regionprops can be used to estimate the area enclosed by each of the boundaries

bw = imfill(bw,"holes");
imshow(bw)

Figure contains an axes object. The axes object contains an object of type image.

Step 4: Find the Boundaries

Concentrate only on the exterior boundaries. Specifying the "noholes" option 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.

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
title("Objects with Boundaries in White")

Figure contains an axes object. The axes object with title Objects with Boundaries in White contains 7 objects of type image, line.

Step 5: Determine which Objects are Round

Estimate the circularity and centroid of all of the objects using the regionprops function. The circularity metric is equal to 1 for an ideal circle and it is less than 1 for other shapes.

stats = regionprops(L,"Circularity","Centroid");

The classification 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.

threshold = 0.94;

Loop over the detected boundaries. For each object:

  • Obtain the (x,y) boundary coordinates and the circularity measurement

  • Compare the circularity measurement to the threshold. If the circularity exceeds the threshold, calculate the position of the centroid and display the centroid as a black circle.

  • Display the circularity measurement in yellow text over the object.

for k = 1:length(B)

  % Obtain (X,Y) boundary coordinates corresponding to label "k"
  boundary = B{k};
  
  % Obtain the circularity corresponding to label "k"
  circ_value = stats(k).Circularity;
  
  % Display the results
  circ_string = sprintf("%2.2f",circ_value);

  % Mark objects above the threshold with a black circle
  if circ_value > threshold
    centroid = stats(k).Centroid;
    plot(centroid(1),centroid(2),"ko");
  end
  
  text(boundary(1,2)-35,boundary(1,1)+13,circ_string,Color="y",...
       FontSize=14,FontWeight="bold")
  
end
title("Centroids of Circular Objects and Circularity Values")

Figure contains an axes object. The axes object with title Centroids of Circular Objects and Circularity Values contains 17 objects of type image, line, text. One or more of the lines displays its values using only markers

See Also

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