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<div class="moz-cite-prefix">Hi Even,<br>
<br>
most of all depends what kind of imagery and maps you wish to
classify. If the maps are classical scanned paper maps, and you
want fast algorithm - the crosses of meter or degree grid can be
the good pattern.<br>
But if we have areal images this will not work, as such images
have crosses too. But satellites - not. May be some frame of maps
can be good pattern.<br>
<br>
If you have some fragment of maps and images, I think some content
analysis needed:<br>
- clustering, i.e. <a class="moz-txt-link-freetext" href="http://en.wikipedia.org/wiki/K-means_clustering">http://en.wikipedia.org/wiki/K-means_clustering</a><br>
-<span style="margin: 0px; padding: 0px; border: 0px; font:
inherit; vertical-align: baseline; outline: 0px;"> Neural</span>
network with learning<br>
-<span dir="auto"> Support vector machine i.e.
<a class="moz-txt-link-freetext" href="http://svmlight.joachims.org/">http://svmlight.joachims.org/</a> and </span><a class="moz-txt-link-freetext" href="http://en.wikipedia.org/wiki/Support_vector_machine">http://en.wikipedia.org/wiki/Support_vector_machine</a><br>
<br>
Also some hash comparison can be used (rather fast)<br>
- perceptual hash compare i.e. <a class="moz-txt-link-freetext" href="http://www.phash.org/">http://www.phash.org/</a><br>
<br>
In all cases input images should be resized to some small sizes
and may be grayscaled or binarized before analysis.<br>
<br>
<pre class="moz-signature" cols="72">Best regards,
Dmitry</pre>
06.03.2014 23:19, Even Rouault пишет:<br>
</div>
<blockquote
cite="mid:201403062019.30124.even.rouault@mines-paris.org"
type="cite">
<pre wrap="">Hi,
I'd be interested in an algorithm to automate the classification of raster data
between maps (let's say rendering of OpenStreetMap data, or other digital
maps) one one side and aerial/satellite imagery on the other side, without
looking at metadata (bare geotiff typically). This is to help in automating
bulk of import of data from a media and establishing a first level of
classification.
Has anyone already done that and has code and/or advice to share, or know a
software project that would do that ?
Some ideas that came to my mind :
- maps have typically a much more reduce number of colors than imagery, but
you may have imagery that has already been transformed to 256 colors to reduce
storage space.
- maps have generally a majority color (e.g. white, green), but not in all
zones (urban zones will have more features)
- maps have higher spatial frequency (lines, text) whereas imagery will be
more continuous : use of gradient, and compute statistics on it ?
Even
</pre>
</blockquote>
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