Identify and track the center of the logical object

after morphological operation.
check if the area of blob is greater than a threshold

sedisk = strel('square',15);
fg = imclose(fg, sedisk);
fg = imfill(fg,'holes');
RLL = bwlabel(fg);

stats = regionprops(RLL,'basic','Centroid');
figure(1),imshow(fr_bw)
hold on

for n = 1:length(stats)
if(stats(n).Area > 100)
plot(stats(n).Centroid(1), stats(n).Centroid(2),'r*')
end
end

Problem: can track less 50% of the cars, however there are too many outiners because of the transformation done during stabilization. also hard to determine the area, i did it using trial and error to get the best fit

Matlab morphological operation

IM2 = imdilate(IM,SE) dilates the grayscale, binary, or packed binary image IM, returning the dilated image, IM2.
IM2 = imerode(IM,SE) erodes the grayscale, binary, or packed binary image IM, returning the eroded image IM2.


The argument SE is a structuring element object or array of structuring element objects returned by the strel function.


The morphological close operation is a dilation followed by an erosion, using the same structuring element for both operations. The morphological open operation is an erosion followed by a dilation, using the same structuring element for both operations.

these operations are performed on a stabilized video sequence done by SIFT. and basic background subtraction.

se1 = strel('square',11) % 11-by-11 square
se2 = strel('line',10,45) % line, length 10, angle 45 degrees
se3 = strel('disk',15) % disk, radius 15
se4 = strel('ball',15,5) % ball, radius 15, height 5


sedisk = strel('square',10);
fg = imclose(fg, sedisk);


sedisk = strel('line',10,90);
fg = imclose(fg, sedisk);

sedisk = strel('line',15,5);
fg = imclose(fg, sedisk);


sedisk = strel('disk',10);
fg = imclose(fg, sedisk);


Deciding on the morphological structure is much harder than deciding on the threshold of background subtraction