Effacer les filtres
Effacer les filtres

detect square in image

47 vues (au cours des 30 derniers jours)
Abdul
Abdul le 29 Déc 2011
Commenté : Dmitry Surov le 16 Sep 2020
i want to detect square shape only in image. how can i do this using matlab?

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Chandra Kurniawan
Chandra Kurniawan le 29 Déc 2011
Hello,
Is your goal only to detect square in this picture?
If so, you don't need to do shape recognition, etc.
You just need to perform some morphologichal operations only.
I = imread('3617ca70.png');
Ibw = ~im2bw(I,graythresh(I));
Ifill = imfill(Ibw,'holes');
Iarea = bwareaopen(Ifill,100);
Ifinal = bwlabel(Iarea);
stat = regionprops(Ifinal,'boundingbox');
imshow(I); hold on;
for cnt = 1 : numel(stat)
bb = stat(cnt).BoundingBox;
rectangle('position',bb,'edgecolor','r','linewidth',2);
end
And the result :
Is this what you need?
  3 commentaires
An Hoang
An Hoang le 9 Avr 2018
Modifié(e) : An Hoang le 9 Avr 2018
thank you so much! How to determine whether a check box option is selected
Dmitry Surov
Dmitry Surov le 16 Sep 2020
Can you please explain what do we get in stat variable ? It's something related to border line of each square, but i misunderstand what that means
Thanks

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Plus de réponses (2)

Sean de Wolski
Sean de Wolski le 29 Déc 2011
Those squares are very well defined.
  • Set a less than threshold to make the dark colors true and everything else false. ( BW = I<thresh )
  • Perform a connected components analysis ( doc bwconncomp)
  • Then regionprops with EulerNumber specified.
  • Apply a threshold to the regions matching the EulerNumber ( idx = [stats(:).EulerNumber] == x ) of a sample square.
  • Build a new matrix of false. ( BWnew = false(CC.ImageSize))
  • Set the indices in the connected components analysis corresponding to the matching EulerNumber to true. ( BWnew(vertcat(CC.PixelIdxList{idx})) = true)
In theory you'll have a mask of the boxes.

Naz
Naz le 29 Déc 2011
Modifié(e) : John Kelly le 14 Nov 2013
I just thought of an alternative idea. Instead of detecting a square, you should register the image (filled form) of interest with the raw image. Then, since you know the coordinates of each square, you can just check the pixels at those coordinates for the white/black values.

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