Detecting 8 connected neighborhood of a object in image

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Dimitris M
Dimitris M 2013-3-1
Hello
I need to find robust method for detecting the 8-connected neighbor of a rectangle-like object in an image.
I was considering something like dilation on the image but this does not seems to detect all the adjacent pixels in every case (considering change of shape) so know I am looking for another approach.
If you have any idea please let me know !
Regards

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回答（2 个）

Matt J
Matt J 2013-3-1
编辑：Matt J 2013-3-1
You mean you have a binary image and you want to detect pixels with 8 neighbours that are "1"? If so,
kernel=[1 1 1; 1 0 1; 1 1 1]/8;
idx = conv(image,kernel,'same')>=.998; %.998 is a tolerance close to 1
and then if you want to, you can convert idx to subscript indices
[I,J]=find(idx);
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Dimitris M
Dimitris M 2013-3-1
Hello
I tried your algorithm but it doesn't seem to work. From what I have seen the conv() function requires vectors as input and the "image" and "kernel" are 2-D arrays !
Is there a way to work this out ?
Thanks again for the feedback
Matt J
Matt J 2013-3-1
编辑：Matt J 2013-3-1
Sorry, I meant conv2.
idx = conv2(image,kernel,'same')>=.998;

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Image Analyst
Image Analyst 2013-3-1
Dmitris:
This is done with bwhitmiss() in the Image Processing Toolbox. Go here to Steve's blog to see examples: http://blogs.mathworks.com/steve/2011/07/08/binary-image-hit-miss-operator/. You just need to look at 4 cases, where the center pixel is true and a single corner is true. All of the other possible 252 cases will be 4 connected or not connected at all.

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