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How to get the binary matrix of an image ?

Asked by Emily on 21 Jun 2012

Dear all, I creat a 2-D network by method of fractal interpolation to simulate soil cracks. In my program ,plot(x,y) which plots the network , x,y stand for the points' corrdinate value. I want to compute this network's fractal dimension, but I can't get this image from the figure plotted. My quentions are how to get this image in jpg. or bmp.without white blank like the figure, and how to get the binary matrix of this figure. Thanks in advance.

0 Comments

Emily

3 Answers

Answer by Image Analyst on 21 Jun 2012
Accepted answer

Emily, If you want an image of your cracks, first I'd create a blank image with zeros(). Then I'd go down through every x,y pair that you have using imline() to draw the line (crack) from one point to the next. Now you have your image with all your cracks on it, and you can use export_fig() to write it out to a standard format image file. This will give you just the image alone - no tick marks and titles etc.

However if you want a plot, rather than an image, I'd continue doing it the way you are and then use export_fig() to get the whole plot - including the title, x and y axis labels, tick marks, outer plot area bounding box, etc.

I don't really see how the image of the cracks is going to help you calculate the fractal dimension of the crack network though. I don't use fractals but I though the fractal dimension of a 2D image would look at all the pixel values of all the pixels to give a metric that is kind of related to the "roughness" of the image, but that wouldn't be appropriate to get the fractal dimension of a binary image of a crack network.

3 Comments

Emily on 22 Jun 2012

Hi, thanks for your answer.
i'm sorry i should have been clearer in my quenstion. Base on statistics of actual cracks, the stages i get the crack network are listed as follws: first, generating random dots according to the actual node density of cracks per m2; second, creating random network based on a relationship of nodes' connection; third, generating inflections between two nodes connected, calculate the corrdinate of the infections; last, according to the nodes and inflections in order, using the fractal interpolation to interpolate, then these dots formede the network. I'm stucked in the last stage, in this stage, the interpolated iterations are decided by fractal dimension of the image i get compared with the actual networks, when the the fractal dimension reaches to the actual, the iteration end, otherwise, continue. Now i don't know how to get the iterations.
Please forgive my poor English, thanks again.

Image Analyst on 22 Jun 2012

It doesn't really seem like an imaging problem, other than you could generate an image or a plot of the crack network, and I'm not a fractal expert so I'm going to bow out. I'm just going to suggest that you edit your post from "How to get the binary matrix of an image ?" to "Determine fractal dimension of network of cracks" so that some fractal experts might find it and help you. Of course they'll also want to see some kind of plot or image like I asked you for earlier so do that now.

Emily on 24 Jun 2012

Thank you very much!

Image Analyst
Answer by Walter Roberson on 21 Jun 2012

getsnap() or getframe(); and then imwrite() or saveas() or print() or use the File Exchange contribution export_fig

You can set the axes background color to something other than white.

10 Comments

Walter Roberson on 22 Jun 2012

Perhaps if you specify the rectangle to capture when you use getframe() ?
http://www.mathworks.com/help/techdoc/ref/getframe.html

Image Analyst on 22 Jun 2012

You're still not as clear as you'd be if you would just upload an image and describe what it is that you want. Mock up some lines on it using Photoshop or whatever to say what part you want to save. Try tinypic.com and pick the last link it give you.

Emily on 24 Jun 2012

Thanks again!

Walter Roberson
Answer by faraz.a on 25 May 2013

please tell me how to create a matrix of zeroes and ones for black and white pixels of a binary image.

1 Comment

Image Analyst on 25 May 2013

One way is to threshold a grayscale image

binaryImage = grayImage > thresholdValue;
faraz.a

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