چکیده (انگلیسی):

Geo-referenced data is required in many Geographic Information
System (GIS) applications and one source of such data being maps.
Meteorological maps are color-coded with different regions corresponding
to different values of a parameter, parsing the image to convert into data is
not very difficult. However, text and different planimetric elements overlaid
on the regions in the map makes accurate image to data conversion a
challenging problem, because it is almost impossible to exactly replace
what was underneath the text or icons i.e., the need for inpainting. In this
study, we propose a probabilistic technique that uses the probability of
occurrence of colors present in the map along with the occurrence of those
colors in the spatial neighborhood of the pixel (corresponding to text)
whose color is required to be replaced. We test the limits of our proposed
technique using simulated data and compare results with a popular image
editing tool using public domain data with promising results.