  Separation of the text regions from background texture and graphics is an
important step of any optical character recognition system for the images
containing both texts and graphics. In this paper, we have presented a novel
text/graphics separation technique and a method for skew correction of text
regions extracted from business card images captured with a cell-phone camera.
At first, the background is eliminated at a coarse level based on intensity
variance. This makes the foreground components distinct from each other. Then
the non-text components are removed using various characteristic features of
text and graphics. Finally, the text regions are skew corrected for further
processing. Experimenting with business card images of various resolutions, we
have found an optimum performance of 98.25% (recall) with 0.75 MP images, that
takes 0.17 seconds processing time and 1.1 MB peak memory on a moderately
powerful computer (DualCore 1.73 GHz Processor, 1 GB RAM, 1 MB L2 Cache). The
developed technique is computationally efficient and consumes low memory so as
to be applicable on mobile devices.
