I believe we were writing emails at the same time, and you didn't get to read my last one.
On 2 March 2010 21:49, Gerald Friedland <fractor@xxxxxxxxx> wrote:
First: Try any image that works well and add 80% noise. SIOX is pretty
good with noise.
Last time I tried Grabcut with such an image, I got a segmentation fault...
Here is an example with heavy noise to show that we can cope with it: http://www.liv.ic.unicamp.br/~tvspina/images/flower_noisy_result.png (original: http://www.liv.ic.unicamp.br/~tvspina/images/flower_original.png).
Once again, I must say that we do not use GrabCut nor any graph-cut-based method. That's why you cannot assume that we have the same weaknesses. In a way we do perform a cut in our graph, but we do not use the min-cut/max-flow algorithm. In fact, a paper by a coleague of mine and my advisor [1] proved that the best result graph-cut can achieve is the one IFT already provides.
Furthermore, although I do believe that being noise resistant is very important, and SIOX does a very good job at it, I do not think that regular GIMP users would want to segment an image with 80% noise.
Then: Try images like this one:
http://www.bigfoto.com/themes/nature/winter/tree-winter-village.jpg
and try to extract the tree. The current GIMP version in the main branch
cannot do it, the version from last Google Summer of Code can do it.
Graph-based algorithms usually have problems but I think this is an
important feature
because it saves HOURS of work to be able to do it semi-automatically!
Given that you probably did not see my previous email, because we exchanged them almost at the same time, you missed the fact that I am working to solve that problem and that I already have a good solution for semi-transparent images. Please refer to my last email for more information. Working with such images is paramount to my research and that problem will not remain unsolved for long. In fact, I believe that within the month or less I should have a good solution ready.
Thiago
--
MSc student
Laboratory of Visual Informatics
Institute of Computing -- Unicamp
www.liv.ic.unicamp.br
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