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task #11175: Submission of The Pink Image Processing Library

Submitter:  Abigail Grove <abigailgrove>
Submitted:  Thu 26 May 2011 09:33:14 PM UTC
   
 
Should Start On:  Thu 26 May 2011 12:00:00 AM UTC Should be Finished on:  Sun 05 Jun 2011 12:00:00 AM UTC
Category:  Project Approval Priority:  * 5 - Normal
Status:  Cancelled Privacy:  Public
Assigned to:  alexfernandez Open/Closed:  Closed
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Sat 11 Jun 2011 09:14:32 PM UTC, comment #2: 

Closing upon request from Laszlo.

Alex Fernandez <alexfernandez>
Mon 30 May 2011 10:51:22 PM UTC, comment #1: 

Hi Abigail,

I am evaluating your submission on behalf of Savannah, sorry for the delay.

We need to review that the source code of the project meets our hosting requirements. Can you provide a tarball? Thanks!

Alex Fernandez <alexfernandez>
Thu 26 May 2011 09:33:14 PM UTC, original submission:  

A new project has been registered at Savannah
This project account will remain inactive until a site admin approves or discards the registration.


Registration Administration


While this item will be useful to track the registration process, approving or discarding the registration must be done using the specific Group Administration page, accessible only to site administrators, effectively logged as site administrators (superuser):



Registration Details


  • Name: The Pink Image Processing Library
  • System Name:  pink-image
  • Type: non-GNU software & documentation
  • License: Other (CeCILL is the first license defining the principles of use and dissemination of Free Software in conformance with French law, following the principles of the GNU GPL. This license is meant to be used by companies, research institutions and all organisations willing to release software under a GPL-like license while ensuring a standard level of legal safety. CeCILL is also perfectly suited to international projects. )





Description:

Pink is an image processing and image analysis library developed at ESIEE Engineering for research and teaching purposes. It is build upon Boost Python and the Python Imaging Library, and uses plug-ins that use python-vtk, numpy and matplotlib. While the core foundation has been in development for over a decade, its Python front-end is recent work.

Most existing image processing libraries concentrate on pixel-based operators and linear filtering methods like convolutions, FIR and IIR filters, diffusion and so on. Pink complements these with implementations of over 200 algorithms for image segmentation and non-linear
filtering. Whereas most operators come from mathematical morphology, discrete geometry and discrete topology, operators from other fields are implemented as well.

The Pink dedicated front end is exposed using Boost Python. The library is designed to behave natively in Python, with the functional programming paradigm. Operators are
functions and the images are returned after the operation as results.

This way complex image processing pipelines and algorithms can be easily scripted in Python. This enables an
easy plugin creation or development of solutions for particular applications (pre-processing—segmentation—post-processing).

The Python front-end makes it suitable to use Pink together with other packages like SAGE, PyLab or Tkinter. This makes it possible to develop image segmentation and processing methods that are using graphical interfaces for parametrization. The operators can
be demonstrated using Python’s facilities in an interactive manner. This functionality is particularly useful as a learning tool.

All the operators feature research-level, scientific journal-described algorithms with 3D extension where possible. Notable operators include skeletonization and topological thinning, mathematical morphology, watershed, maximum flow, total variation filtering, and more.

From the technical point of view, the images in Pink are exposed in Python as objects. The operators are functions, with images as first parameters. As result, they return a processed image. Pixels, if necessary, can be accessed with intuitive operators. This means that simple algorithms for experimenting can be implemented directly in Python with speed as the only constraint.

By design new C/C++ operators can be exposed using only a few lines of C++ code, completely omitting third party languages. Indeed, the complete library is implemented using
C/C++ and Python. It has been ported to most of the popular Linux distributions and it also runs on OSX and Microsoft Windows.

The software is open-source and freely available. It is currently soliciting new users and developers.



Other Software Required:

For optimal use, the following packages should be installed:

imview GPL
Python Python license
Doxygen GPL
ActiveTcl 8.3 GPL
VTK GPL
MPlayer GPL
Gnuplot Gnuplot license


Tarball URL:

pinkhq.com


Abigail Grove <abigailgrove>

 

(Note: upload size limit is set to 16384 kB, after insertion of the required escape characters.)

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Depends on the following items: None found

Items that depend on this one: None found

 

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  • -email is unavailable- added by alexfernandez (Posted a comment)
  • -email is unavailable- added by abigailgrove (Submitted the item)
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    Follow 4 latest changes.

    Date Changed by Updated Field Previous Value => Replaced by
    2011-06-11 alexfernandez StatusIn Progress Cancelled
        Open/ClosedOpen Closed
    2011-05-30 alexfernandez StatusNone In Progress
        Assigned toNone alexfernandez

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