[gdal-dev] Heuristics to classify raster data ?

[Even Rouault]

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

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