ITK Implementation Of The Minimum Error Image Thresholding Algorithm
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Please use this identifier to cite or link to this publication: http://hdl.handle.net/1926/1506
An implementation of the minimum error thresholding algorithm is presented. In this implementation, two versions of the minimum error thresholding algorithm are made available, one utilizing a Gaussian- and the other utilizing a Poisson- mixture model. Two ITK classes are created: The first one (MinErrorThresholdImageCalculator) is used to compute the threshold; the second (MinErrorThresholdImageFilter) is used as an image-thresholding filter. The results indicate code correctness and are comparable to those of Otsu’s thresholding algorithm.
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minus A useful automatic threshold detection by Gaetan Lehmann on 2009-01-03 17:11:54 for revision #1
starstarstarstarstar expertise: 4 sensitivity: 5
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Summary:

The author describe an automatic threshold computation method called Minimum Error
Image Thresholding Algorithm and the implementation he made and compare it to the Otsu's one.

Open Science:

The source code is provided as well as the input images.

Reproducibility:

I've been able to download, build and run the code with the test program. I haven't been able to validate the result produced, as the author doesn't provide the output images. I would suggest checking output image in the test. This can be acheived easily with itkTestDriver with the following lines:

FIND_PROGRAM(ITK_TEST_DRIVER itkTestDriver)
SET(TEST_COMMAND ${ITK_TEST_DRIVER} --add-before-env PATH ${CMAKE_BINARY_DIR})

ADD_TEST( Test ${TEST_COMMAND} ${CurrentExe}
          ${CMAKE_SOURCE_DIR}/images/input.png out.png
          --compare out.png ${CMAKE_SOURCE_DIR}/images/test.png
)

Open source Contributions:

The code is built on the same model than ITK's Otsu filter, and the specific parts are well described, so it is easy to use.

Code Quality :

The code is quite nice and easy to read and should run without problems on any platforms supported by ITK.

Interest:

Automatic threshold method are very useful in many domains. Having many of them make possible to chose the best one for a segmentation task. Also, this method is a reference in automatic threshold computation. It's a must have for method comparisons.

Free comment :

Just a few comments:



  • Otsu filter use a strange convention used only in that filter in ITK: the background in white and the foreground black. You should prefer the one used elsewhere: the background in black and the foreground white

  • ITK's naming convention requires to avoid abbreviations, so MinError should be replaced by MinimumError

  • an enum would be easier to represent the distribution used, and would make easier the implementation of another distribution (if possible) than the m_UseGaussian and m_UsePoisson vars

  • check the output images as suggested before


great contribution!

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Categories: Filtering, Segmentation
Keywords: Minimum error thresholding, Otsu thresholding
Toolkits: ITK, CMake
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