[GRASS-dev] FW: FW: OSGeo-SoC 2016 application

[Moritz Lennert]

Dear Bo,

Thanks for the document. I have to give classes now, but will try to 
read while the students work ;-)

Apparently, I was not concentrating while writing some of my mails: 
split-window is not a segmentation algorithm. Sorry about that. I meant 
general (top-down) image splitting algorithms, such as quad-tree, etc.

BTW, maybe there was a misunderstanding: you spoke about dynamic 
thresholding and markov random field (MRF) for classification. I'm no 
expert on these, but AFAIK, they are also used for segmentation. So, 
while my remark concerning classification remains true, don't hesitate 
to integrate these algorithms into the segmentation part, if you want to.

Moritz

On 25/03/16 06:21, Yang, Bo (yangb2) wrote:
> Dear Moritz,
>
> Please find the attachment for my first draft of the proposal.
> GoogleDoc:
> https://docs.google.com/document/d/1Qanh7sUdJZfiusTVIBHmlbC6NY9kKFVR18OL3icreoM/edit?usp=sharing
>
> Thanks for your advices, such as Orfeo Toolbox, those are really helpful
> for further understanding the segmentation algorithms.
>
> However, I find few literature about the split-window algorithm, So for
> the time being I put mean-shift and watershed as my highest priority
> algorithm to be implemented.
>
> Please let me know if you and/or Markus have any suggestions. I didn't
> strictly follow the proposal template[1] because there is no methods
> part. I restructure the proposal and included all the required
> information in the template. If needed I can revise it to exactly follow
> template's format. The proposal is due tomorrow afternoon for me (3pm
> EST) so I think I still have enough time to refine it.
>
> Yes, I fully understand there is no guarantee that the proposal will be
> accepted, and I am totally fine with it. Thanks for pointing it out. Be
> engaging in the GSoC process is more valuable for me since I've learning
> about groups of people that extend beyond just GSoC. I will try my best.
>
> Best regards,
>
> Bo Yang
>
> [1]
> https://wiki.osgeo.org/wiki/Google_Summer_of_Code_Recommendations_for_Students#Application_questions_we.27ll_ask_you
>
> -----Original Message-----
> From: Moritz Lennert [mailto:mlennert at club.worldonline.be]
> Sent: Thursday, March 24, 2016 7:52 AM
> To: Yang, Bo (yangb2) <yangb2 at mail.uc.edu>; Luca Delucchi
> <lucadeluge at gmail.com>
> Cc: grass-dev at lists.osgeo.org; Markus Metz <markus.metz.giswork at gmail.com>
> Subject: Re: [GRASS-dev] FW: FW: OSGeo-SoC 2016 application
>
> Dear Bo,
>
> On 24/03/16 06:26, Yang, Bo (yangb2) wrote:
>
>  > Dear Moritz,
>
>  >
>
>  > Thank you for the reply, and thanks you and Markus could be the mentor
>
>  > of the i.segment project! There are only two days left for submitting
>
>  > the proposal, take into consideration I think I need to switch to the
>
>  > topic of i.segment project now.
>
> Thank you for the flexibility !
>
>  > For my cokriging fusion
>
>  > topic I think I could do it after this summer in the future work.
>
> Great !
>
>  > I've read the source code and Eric's wiki of GSoC 2012 [0]. I think I
>
>  > will prepare the proposal following the direction of adding new
>
>  > algorithms to segment an image into objects-- more than region-growing
>
>  > algorithm. Moritz, you mentioned segmentation
>
>  > algorithm: mean-shift, split-window and watershed.
>
> Yes, as the general logistics of the i.segment module is in place,
> adding new segmentation algorithms should not be too hard, so adding
> several should be possible during this GSoC.
>
>  > I think some
>
>  > unsupervised classification algorithms would also be possible such
>
>  > as: dynamic thresholding and markov random field (MRF).
>
> Unsupervised classification could be an interesting addition.
>
> However, I would think KISS. So, concentrate on the segmentation. You
> can add classification in the the project as a possible extension, in
> case you finish early with the segmentation.
>
> In any case, classification should be a separate module. The idea is to
> have each module do one thing. Currently classification is proposed by
> v.class.ml and v.class.mlR (but the latter is a very simple hack I did
> for teaching - I'm currently busy rewriting it), but they are supervised.
>
> For classification segment characterization is also important. Currently
> we have two Python-based modules for that v.class and i.segment.stats.
>
> One option might be to think about more efficient approaches and more
> variables for that.
>
>  > If you think
>
>  > it is OK, I will start the preparing the draft of proposal from now
>
>  > on, and I think I could have the first version send back to you by
>
>  > tomorrow (Thursday).
>
> Perfect. Markus and I are in Europe so don't forget about time zones
> when thinking about when to send us your draft...
>
>  > If you have any suggestions and comments please let me know.
>
> Markus can give you more details about the actual implementation. I
> think in your proposal you should show that you have a general idea of
> how i.segment works, and you should review different segmentation
> techniques, possibly with relevant literature references. You might also
> want to have a look at Orfeo Toolbox and their implementation of some of
> the segmentation algorithms.
>
> In general, it would be nice to add at least one or two top-down methods
> as this would allow top-down hierarchical segmentation, while the
> current region growing approach only allows bottom-up hierarchical
> segmentation.
>
> Final note just to make sure that this is clear: please be aware that
> there are other GRASS-related proposals and that we do not know how many
> slots we will get for GRASS. There is thus no guarantee that your
> proposal will be chosen.
>
> Best wishes,
>
> Moritz
>