Detecting square object could be done in similar way we used to detect the round object. What we need to know is just the the formula for the area and the perimeter of a square object which is A = w^2 and P = 4*w.
1. Original image and the negative image (value 0 represent background while 1 represent oject).
S = imread('pic10.jpg');
S = im2bw(S);
S2 = ~S;
2. Labeling the objects in the image. The advance programming language will support this function and label the objects.
S3 = bwlabel(S2);
3. Some properties of the objects are extracted using the command. In this example, we just use the area and perimeter for our calculation.
S4 = regionprops(S3,'Area','Perimeter','centroid');
4. Now, evaluate the "squareness" of the objects. this is evaluated by only 1 criteria in this example:
a. Calculate the length or width of the object by using the formulas of area and perimeter, comparing the result and the square objects would have higher score than others. Do note that instead of for loop, the code below is a vectorized code.
score = (min(sqrt([S4.Area]),[S4.Perimeter]/4)./(max(sqrt([S4.Area]), ...[S4.Perimeter]/4))).^2;
5. Display the result visually
for cnt = 1:length(S4)
Do note that this example assumes perfect images. For more accurate results, more properties can be compared by using more criteria. The example above is done using MATLAB®.
MATLAB® is registered trademarks of The MathWorks.