Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Text/Graphics Separation for Business Card Images for Mobile Devices   Separation of the text regions from background texture and graphics is an
important step of any optical character recognition sytem for the images
containg both texts and graphics. In this paper, we have presented a novel
text/graphics separation technique for 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 and binarized for further processing. Experimenting with
business card images of various resolutions, we have found an optimum
performance of 98.54% 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.

34
The categories of this paper are: chem-ph
15
The categories of this paper are: nucl-ex
6
The categories of this paper are: astro-ph
7
The categories of this paper are: hep-th
18
The categories of this paper are: econ
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The categories of this paper are: funct-an
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The categories of this paper are: q-alg
20
The categories of this paper are: acc-phys
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The categories of this paper are: cmp-lg
9
The categories of this paper are: nlin
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The categories of this paper are: mtrl-th
26
The categories of this paper are: bayes-an
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The categories of this paper are: comp-gas
4
The categories of this paper are: cond-mat
25
The categories of this paper are: patt-sol
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The categories of this paper are: q-fin