The purpose of this paper is to propose a new multi
stage algorithm for the recognition of isolated characters. It was similar work
done before using only the center of gravity (This paper is
extended version of “A fast recognition system for isolated printed characters using
center of gravity”, LAP LAMBERT Academic Publishing 2011, ISBN: 978-38465-0002-6), but here
we add using principal axis in order to make the algorithm rotation invariant.
In my previous work which is published in LAP LAMBERT, I face a big problem
that when the character is rotated I can’t recognize the
character. So this adds constrain on the document to be well oriented but here I use the
principal axis in order to unify the orientation of the character set and the
characters in the scanned document. The algorithm can be applied for any
isolated character such as Latin, Chinese, Japanese, and Arabic characters but
it has been applied in this paper for Arabic characters. The approach uses
normalized and isolated characters of the same size and extracts an image signature
based on the center of gravity of the character after making the character
principal axis vertical, and then the system compares these values to a set of
signatures for typical characters of the set. The system then provides the
closeness of match to all other characters in the set.
Cite this paper
A. Shaffie and G. Elkobrosy, "A Fast Recognition System for Isolated Printed Characters Using Center of Gravity and Principal Axis," Applied Mathematics, Vol. 4 No. 9, 2013, pp. 1313-1319. doi: 10.4236/am.2013.49177.
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