Bologna University/Image Acquisition and Elaboration

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'''Image Acquisition'''
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Using the experimental set up illustrated [http://2007.igem.org/Bologna_University/Microscopy:_Experimental_Set_Up here], we obtain short film segments of our fluorescent bacteria; then, with an apposite software, we extract several frames from each of them. Examples of images we get are shown below.
Using the experimental set up illustrated [http://2007.igem.org/Bologna_University/Microscopy:_Experimental_Set_Up here], we obtain short film segments of our fluorescent bacteria; then, with an apposite software, we extract several frames from each of them. Examples of images we get are shown below.
[[Image:orig1.jpg|center]]  
[[Image:orig1.jpg|center]]  
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[[Image:orig22.jpg|center]]
[[Image:orig22.jpg|center]]
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'''Image Elaboration'''
Since we need to know how much of the total image area is occupied by bacteria, we process the images with our segmentation algorithm implemented in Matlab.
Since we need to know how much of the total image area is occupied by bacteria, we process the images with our segmentation algorithm implemented in Matlab.

Revision as of 13:57, 19 October 2007

Image Acquisition

Using the experimental set up illustrated here, we obtain short film segments of our fluorescent bacteria; then, with an apposite software, we extract several frames from each of them. Examples of images we get are shown below.


Orig1.jpg
Orig22.jpg


Image Elaboration

Since we need to know how much of the total image area is occupied by bacteria, we process the images with our segmentation algorithm implemented in Matlab.

Here are the processing phases:

  • the RGB image is read and the green channel is extracted;
  • a morphological top hat filtering is performed on the grayscale image;
  • by means of an adaptive threshold, the image is tranformed in a binary one;
  • the distance between every point and the nearest black pixel is calculated;
  • on this last image the watershed algorithm is applied: every pixel is assigned a label, depending on the segmentated region it belongs; then, every labeled region is represented with a different colour, as in the images shown below.


Segm1.jpg
Segm2.jpg







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