  We present a hierarchical method for segmenting text areas in natural images.
The method assumes that the text is written with a contrasting color on a more
or less uniform background. But no assumption is made regarding the language or
character set used to write the text. In particular, the text can contain
simple graphics or symbols. The key feature of our approach is that we first
concentrate on finding the background of the text, before testing whether there
is actually text on the background. Since uniform areas are easy to find in
natural images, and since text backgrounds define areas which contain "holes"
(where the text is written) we thus look for uniform areas containing "holes"
and label them as text backgrounds candidates. Each candidate area is then
further tested for the presence of text within its convex hull. We tested our
method on a database of 65 images including English and Urdu text. The method
correctly segmented all the text areas in 63 of these images, and in only 4 of
these were areas that do not contain text also segmented.
