Pattern and object recognition with COSFIRE
George Azzopardi
geazzo at gmail.com
Wed Dec 17 05:48:26 EST 2014
Dear all,
I am pleased to see interest in the COSFIRE approach that I started during
my PhD studies.
The COSFIRE approach is a trainable pattern recognition approach which can
be applied to several applications, including feature detection, object
recognition and localization, image classification, contour detection and
vessel segmentation. The selectively for a pattern of interest is
automatically configured in a training process. The method involves several
computations that are independent of each other, and thus it can be easily
implemented using parallel programming (e.g. on a GPU). The original paper
(http://www.cs.rug.nl/~george/articles/PAMI2013.pdf) combines information
about the contours of the concerned pattern. We now have another paper
which is currently being reviewed for CVPR2015 where we show that by adding
colour information COSFIRE filters become even more robust.
Please feel free to send me other ideas on how this work can be developed
further.
I would be very happy and available to work with an undergraduate or a
postgraduate student (or any other person) to have this parallel
implementation in Python. I see that you already added it to the
Requested-features page. You can also add my contact details (geazzo at gmail)
there for the interested readers.
All my papers can be freely downloaded from my
website: http://www.cs.rug.nl/~george/research-activities/
regards,
George
On Tuesday, 16 December 2014 15:22:45 UTC+1, Stefan van der Walt wrote:
>
> On Tue, Dec 16, 2014 at 1:57 PM, Pratap Vardhan <prat... at gmail.com
> <javascript:>> wrote:
> > I found few copies of the paper hosted by universities. I haven't
> checked if
> > these are the actual pre-prints - However, by the citation it looks like
> it.
>
> Thanks! I've added it to the list:
>
> https://github.com/scikit-image/scikit-image/wiki/Requested-features
>
> Stéfan
>
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