Is it possible to bridge more than one pixel in MATLAB? - matlab

I have several lines in a binary image. I know the code bridgeBW = bwmorph(closeBW, 'bridge'); will connect the lines if they are close enough, but so far I've only seen it do that in a one pixel range. Is there a way to increase the distance and bridge lines that are farther away?

I ended up using a line based strel method instead of one defined by a shape.

Related

Morphological operation to improve the shape of segmented image

I have an ellipse in the image.After segmentation i got a broken ellipse as shown .which morphological operation is used to get the perfect ellipse
Actual input file is
output obtained is
i tried imopen ,but i will lose lower ellipse like structure .how to close the upper ellipse like structure without losing lower ones
Mask i created is
i want to segment the ellipse like structure.but some of these structures are connected with rectangular like bodies.how to separate it. erode will eliminate small ellipses
If you want to reconnect something with a mathematical morphology operator, do not use an opening (it increases the gap), but a closing (imclose)! The names are explicits.
In you case, you want to reconnect something vertically cut, so use a horizontal structuring element (type segment).
And yes, you have to invert your image, black pixels representing the absence of information.
Usually, for closing gaps, you would need the close operator.
However, since most software assume active pixels are white, you would either need to invert the image, or use the open operator.
On this image, in matlab, the following works well:
imopen(I,ones(32))
This uses a square structuring element. You may want to experiment with other shapes.
Your example also looks like you moved half of the ellipse, as opposed to some process which deleted pixels in the middle. No simple morphological operation can create a perfect ellipse out of the sample image, unless you use the knowledge that multiple components can be moved to re-form the ellipse. If that is the actual case, you can scan connected components and try to match them together.

Separation of Overlapping and Touching Lines

Can anyone suggest an approach or method for the separation of overlapping and touching lines within handwritten documents?
I can segment text lines. Now i want to separate the connected lines.
Here it is my image:
Thanks
You try using the watershed over the distance function of the connected component set to separate them like here and here. Though its possible it could oversegment the result based on the shapes.

find a distance between object in binary image

I have a binary image with two white vertical segments separated by a small gap. I would like to calculate the distance between the two segments. Or better the gap.
My first attempt: find the profile of the two segments (using bwboundary and bwtraceboundary) and then find the intersection between this profile with horizontal line scanning the whole image. The number of lines without intersection represents the distance between the two segments.
I would like to find this gap without detecting the profile. Is there a way?
Thank you.
You can use measuretool from the MATLAB File Exchange by Jan Neggers to retrieve geometrical information of images.

Line detection using PIL

Given an image consisting of black lines (a few pixels wide) on white background, what is a good way to find the coordinates along the the lines, say for every 10th pixel or so? I am considering using PIL for the task, but other python or java-based libraries would also be OK.
Ideally the coordinates would point to the middle of the line, but as the lines are narrow, it's enough that they point somewhere inside the line.
A very short line or a point should be identified with at least one coordinate.
Usually, Hough transformation is used to find lines. It gives you the parameters describing the line (which can be transformed easily between different representations), and you can sample this function to get your sample points. See http://en.wikipedia.org/wiki/Hough_transform and https://stackoverflow.com/questions/tagged/hough-transform+python
I only found this http://coding-experiments.blogspot.co.at/2011/05/ellipse-detection-in-image-by-using.html implementation in python, which actually searches for ellipses.

Using imtophat in MATLAB

I'm trying to do top hat filtering in MATLAB. The imtophat function looks promising, but I have no idea how to use it. I don't have a lot of work with MATLAB before. I am trying to look find basically small spots several pixels wide that are local maxima in my 2 dimensional array.
I think you have more problem undertanding how to use STREL, than IMTOPHAT. The later can be described as simple threshold but per structural element, not the whole image.
Here is another good examples of using STREL and IMTOPHAT:
http://www.mathworks.com/matlabcentral/fx_files/2573/1/content/html/R14_MicroarrayImage_CaseStudy.html
This series of posts on Steve Eddins blog might be useful for you:
http://blogs.mathworks.com/steve/category/dilation-algorithms/
tophat is basically an "opening" procedure followed by a subtraction of the result from the original image. the best and most helpful explanation of opening I've found here:
http://homepages.inf.ed.ac.uk/rbf/HIPR2/morops.htm
"The effect of opening can be quite easily visualized. Imagine taking
the structuring element and sliding it around inside each foreground
region, without changing its orientation. All pixels which can be
covered by the structuring element with the structuring element being
entirely within the foreground region will be preserved. However, all
foreground pixels which cannot be reached by the structuring element
without parts of it moving out of the foreground region will be eroded
away."
The documentation on imtophat has an example .. did you try it? The following images are from the MATLAB documentation.
Code
I = imread('rice.png');
imshow(I)
se = strel('disk',12);
J = imtophat(I,se);
figure, imshow(J,[])
Original
(image source: mathworks.com)
Top Hat with a disk structuring element
(image source: mathworks.com)