Steve on Image Processing

August 20th, 2008

Image visualization using transparency

Transparent graphics objects can be used effectively to visualize image processing concepts. Two particularly useful techniques are:

  • Highlighting image regions with transparent patches
  • Displaying one image transparently over another

Today I'll show how to highlight image regions with patches. For this example I'll use the 'Extrema' measurement returned by regionprops. The extrema for a given object are eight points: the left-most pixel on the bottom, the right-most pixel on the bottom, the top-most pixel on the right, the bottom-most pixel on the right, and so on.

I'll start with the rice image, segmenting it using techniques I've shown before.

I = imread('rice.png');
imshow(I)

Even out the illumination with the tophat operator, threshold, and then clean up the thresholded image a bit.

I2 = imtophat(I, ones(15, 15));
bw = im2bw(I2, graythresh(I2));
bw2 = bwareaopen(bw, 5);
bw3 = imclearborder(bw2);
imshow(bw3)

Label the binary objects and compute the extrema.

L = bwlabel(bw3);
s = regionprops(L, 'Extrema');

Each object has 8 extrema points associated with it.

s(1).Extrema
ans =

   11.5000   86.5000
   12.5000   86.5000
   34.5000  100.5000
   34.5000  102.5000
   33.5000  103.5000
   27.5000  103.5000
    9.5000   89.5000
    9.5000   87.5000

We can superimpose the extrema-bounded shapes on top of the original rice image by using patch objects.

imshow(I)

hold on
for k = 1:numel(s)
    x = s(k).Extrema(:,1);
    y = s(k).Extrema(:,2);
    patch(x, y, 'g')
end
hold off

The above visualization is pretty clear. If you zoom in on some of the odd, larger shapes, though, you can't really tell what's going on. 

axis([120 200 1 75])

We solve that by displaying the patches transparently.

imshow(I)

hold on
for k = 1:numel(s)
    x = s(k).Extrema(:,1);
    y = s(k).Extrema(:,2);
    patch(x, y, 'g', 'FaceAlpha', 0.3)
end
hold off

Now if you zoom in on the same region, we can see exactly what caused the unusual region.

axis([120 200 1 75])

Two of the rice grains were touching.

Next time I'll show a couple of techniques for visualizing one image transparently superimposed on another.


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15:34 UTC | Posted in Uncategorized | Permalink |

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12 Responses to “Image visualization using transparency”

  1. Cara Schiek replied on October 11th, 2008 at 01:08 UTC :

    Hi.

    How could I do this same thing with image vales within the patches?

    cara

  2. Steve replied on October 11th, 2008 at 18:27 UTC :

    Cara—I do not understand your question. Can you clarify it?

  3. Cara replied on October 12th, 2008 at 22:45 UTC :

    Hi.

    Sorry for the confusion. I would like to produce an image with a transparency similar to what you have done here. Except I would to fill the patches with data from another image. For example, I would like to make a transparency made of patches, where the patches are filled with elevation data. I would like to then overlay the patch transparency onto another image.

    cara

  4. Steve replied on October 15th, 2008 at 14:51 UTC :

    Cara—You can use your elevation data as a texture map on a flat surface object. You might want to take a look at the texture mapping section in the MATLAB 3-D visualization doc, or at the doc for surface properties.

  5. DP replied on February 17th, 2009 at 15:33 UTC :

    Hi Steve,
    As you shown in your example above you have connected two objects on the image, i want to do the opposite, can we seperate the connected two or more objects, in the image?
    thanks
    sincerely
    DP

  6. Steve replied on February 18th, 2009 at 02:23 UTC :

    DP—Check out the segmentation demos in the Image Processing Toolbox.

  7. abc replied on October 4th, 2009 at 00:47 UTC :

    Hi Steve,
    Thanks for all your helpful tutorials. I have a problem trying to overlay a PET image with gray colormap onto a CT image with hot colormap. My data set is unit16. I am SUCCESSFULLY able to overlay the images but the background CT image is VERY unclear/dark (hardly visible). My code looks like this…. Kindly advise

    I_CT = Load CT_IMAGE;
    imshow(I_CT,’displayrange’,[]); colormap(gray)
    I_PET = Load PET_IMAGE;
    hold on
    imshow(I_PET,’displayrange’,[]); colormap(hot)
    set(I_PET_h,’alphadata’,0.5)
    hold off

  8. abc replied on October 4th, 2009 at 03:26 UTC :

    Hi again, i could successfully show PET and CT image in 2 different axes in one figure, but still having difficulty seeing the background CT image after overlaying them. please help. Thanks in advance

  9. Steve replied on October 5th, 2009 at 14:55 UTC :

    Abc—You could try varying the display range for I_CT and also the ‘AlphaData’ parameter.

  10. abc replied on November 14th, 2009 at 16:32 UTC :

    Hi Steve, Thanks for all your previous inputs. i have another problem. i have a volume similar to as shown in this link.

    http://www.mathworks.se/products/matlab/demos.html?file=/products/demos/shipping/matlab/transpdemo.html

    When i using the alpha a value to 0.3 to visualise the inner structure similar to that in the above link . Now I want to calculate the surface area of that inner structure ONLY. Is that possible, and how do i go about finding it.

    Thanks a lot

  11. abc replied on November 14th, 2009 at 23:55 UTC :

    Hi,
    i am successful in finding the total surface area, but i am not able to differentiate the out faces from inner faces ?

    thanks

  12. Steve replied on November 16th, 2009 at 15:35 UTC :

    Abc—I don’t know how to distinguish the faces. You might try posting your question in the MATLAB newsgroup.

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About

Steve Eddins manages the Image & Geospatial development team at The MathWorks and coauthored Digital Image Processing Using MATLAB. He writes here about image processing concepts, algorithm implementations, and MATLAB.

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Recent Comments

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  • Nishtha: Sir, I have preprocessed the image in following steps: [1] adaptive histogram equalization [2] thresholding...
  • Kristof: I also strongly support the idea. I have just recently bumped into the problem that im2single was not...
  • Steve: David—I’ m glad you found it useful!
  • David Lalejini: I found your example very useful for finding connected nodes in a large set of input pairs. I start...
  • tommy: Dear Steve, I have a question,please if you are kind to help me regarding the accumulator array dimensions of...
  • Steve: Abc—I don’t know how to distinguish the faces. You might try posting your question in the MATLAB...
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  • Steve: Manju—What do you mean? How is each region defined?
  • Manju: if we have 2-3 regions within each other how do we measure the regions of each one?

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