A Fast Recognition System for Isolated Printed Characters Using Center of Gravity and Principal Axis

Abstract

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.

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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.

Conflicts of Interest

The authors declare no conflicts of interest.

References

[1] F. Nouboud and R. Palmondon, “On-Line Recognition of Handprint Characters,” Pattern Recognition, Vol. 23, No. 9, 1990, pp. 1031-1044. doi.org/10.1016/0031-3203(90)90111-W
[2] J. Cowel and F. Hussain, “A Fast System for Isolated Arabic Characters,” Proceeding of the 6th International Conference on information Visualisation IEEE, London, July 2002, pp. 650-654.
[3] T. Nawaz, S. A. H. S. Naqvi, H. Rehman and A. Faiz, “Optical Character Recognition System for Urdu (Naskh Font) Using Pattern Matching Technique,” International Journal of Image Processing, Vol. 3, No. 3, 2009, pp. 92104.
[4] J. Cowel and F. Hussain, “Thinning Arabic Characters for Feature Extraction,” IV 2001 Proceedings IEEE Conference on Information Visualization 2001, London, July 2001.
[5] J. Cowell and F. Hussain, “The Confusion Matrix: Identifying Conflicts in Arabic and Latin Character Recognition,” CGIM 2000, Las Vegas, 2000.
[6] J. Cowell and F. Hussain, “Resolving Conflicts in Arabic and Latin Character Recognition,” 19th Eurographics UK Conference, London, April 2001.
[7] M. Al-A’ali and J. Ahmed, “Optical Character Recognition System for Arabic Text Using Cursive Mutli-Directional Approach”, Journal of Computer Science, Vol. 3, No. 7, 2007, pp. 549-555.
doi.org/10.3844/jcssp.2007.549.555.

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