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OCR For Script Identification of Devanagiri Character Set Using Halftoned Image With OPTICS

M. N. Vijayalakshmi, Andhe Dharani, Dr. R. Vasantha, Dr. P. S. Satyanarayana

Abstract


In Optical Character Recognition [OCR], machine printed or handwritten characters/numerals are recognized. Identification of Indian languages scripts which are handwritten is a challenging task. This paper proposes a recognition scheme for handwritten Hindi (devnagiri) characters; most admired one in Indian subcontinent Our work focused on a extracting the features of the colored halftoned handwritten isolated numeral image using the clustering algorithm. These feature vectors are fed to neural classifier model that has been trained to recognize a Hindi numeral. The prototype of system has been tested on varieties of image of isolated characters. Experimentation result shows that memory utilization of colored halftoned images is better compared to original images and the recognition rate is nearly equivalent.


Keywords


OCR, Color Halftoning , clustering, OPTICS

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References


Hussain & Kabuka M.R, “A novel feature recognition Neural network & its application to character recognition”, IEEE TRANS, PAML, Volume 16, 1994,pp-98-106.

Mantas,J (1986), An overview of character recognition Methodologies, Pattern recognition,19(1986)425-430.

R. V. Klassen, R. Eschbach, “Vector Error Diffusion in a Distorted Color Space”, in Proc. IS&T's 47th Annual Conf., 1994.

Jonas Gomes and Luiz Velho, - “Image processing for computer Graphics”, Springer-verlarg, New york, Inc, 1997

M.Ankerest,M.M.Breunig,H.P.Kriegel, andSander, “OPTICS: Ordering Points To Identify the Clustering Structure”, Proc.ACM SIGMOD’99,Int.Conference on Management of Data, Philadelphia, 1999,pp 49-60.

Alessandro Vinciarelli(2002,A survey on offline cursive word recogniton pattern recognition ,35:1433

Ahmed,S.M,et.al,(nov.1995)Experiments in character recognition to develop tools For an optical character recogntion system,IEEE inc.1st National multi topic conf proc.nust ,rawalpindi,pakistan,61-67

Alexandre lemieux,christian gagne & marc Parizeau (2002).Genetically Engineering of Handwriting Representations proc. of the international workshop on frontiers in handwriting Recognition (IWFHR),Nigagara-on-lake.August 6-8

Bortolozzi,F., Britto Jr,.A Oliveira,L.S and Morita,M.,(2005, recent Advances in handwriting Recognition. in umapada pal et al editors,Documnet Analysis,1-31.

Gader P.D .,Forester B., Ganzberger M., A. Bilies,B Mitchell,M .Whalen,T Youeum(1991).Recognition of handwritten digits using template & model matching.Pattern recognition ,5(24):421-431.

Govinda,V.K & Shivaprasad,A P (1990),Character recognition-a review, Pattern recognition .23:671-683.

Hebert Jean-Francois,Parizeau Marc & Nadia Ghazali(1998).A new fuzzy geometirc represenation for on-line isolated character recognition.proc of 14th international conference on Pattern recognition,Brisbane:1121-1123

Banashree N. P., Andhe Dharani, R. Vasanta, P. S. Satyanarayana, “OCR for Script Identification of Hindi (Devnagari) Numerals using Error Diffusion Halftoning Algorithm with Neural Classifier” Proceedings of World Academy of Science, Engineering and Technology Volume 20 April 2007 ISSN 1307-6884, pp. 46 -50

Suen, C.Y .,Berthod, M., & Mori,S (1980), Automatic Recognition of hand printed character-the state of atr, proceeding of IEEE.68(1980) 469-487.

Nouboud,F., & Plamondon,(1990).Online Recognition of hand printed chracter:survey and beta tests,pattern recognition,23:1031-1044

Plamondon Rejean, & sargur N,Srihari,(2000),On line & off line handwriting recognition: A comprehensive survey IEEE Transactions on PAMI.22(63-8.)

T. Mitsa, K.J. Parker, "Digital Halftoning Technique using a Blue-Noise Mask”, J.Opt.Soc.Am A 9(11), 1992, pp. 1920 1929.

V. Ostromoukhov, R.D. Hersch, I. Amidror, “Rotated Dispersed Dither: a New Technique for Digital Halftoning”, ACM Siggraph’94 Conference Graphics Proceedings, Annual Conference Series, 1994, pp. 123-130.

R. Eschbach, “Reduction of artifacts in Error Diffusion by means of Input-Dependent Weights”, Journal of Electronic Imaging, Vol.2 , No. 4, October 1993, 352-358.

H. Haneishi, N. Shimoyama,Y. Miyake, “Color Digital Halftoning for Colorimetric Color Reproduction”, Proc. IS&T, 10th International Congress on Advances in Non-Impact Printing Technologies, 1994, reprinted in Recent Progress in Digital Halftoning, (Ed. R. Eschbach), IS&T, 1994, pp. 9-14

R.L. Miller, R.A. Morton (inventors), “Image Processor with Smooth Transitioning between Dither and Diffusion Processes,” US Patent 5'014'333, issued May 7, 1991, filed Jul. 21, 1988.

J.R. Sullivan, R.L. Miller, T.J. Wetzel (inventors), Color Digital Halftoning With Vector Error Diffusion, US Patent 5 070 413, issued Dec 3rd, 1991, filed Oct 10, 1989.

I. Witten and E. Frank. Data Mining.

T. Graepel. Statistical physics of clustering algortihms. Technical Re- port 171822, FB Physik, Institut fur Theoretische Physic, 1998.

Richards A. J.: “Remote Sensing Digital Image Analysis.An Introduction”, 1983, Berlin, Springer Verlag.

Ng R. T., Han J.: “Efficient and Effective Clustering Methods for Spatial Data Mining”, Proc. 20th Int. Conf. on Very Large Data Bases, Santiago, Chile, Morgan Kaufmann Publishers, San Francisco, CA, 1994, pp. 144-155.

Knorr E. M., Ng R.T.: “Finding Aggregate Proximity Relationships and Commonalities in Spatial Data Mining,” IEEE Trans. on Knowledge and Data Engineering, Vol. 8, No. 6, December 1996, pp. 884-897.

Ester M., Kriegel H.-P., Sander J., Wimmer M., Xu X.: “Incremental Clustering for Mining in a Data Warehousing Environment”, Proc. 24th Int. Conf. on Very Large Data Bases, New York, NY, 1998, pp. 323-333.

Ester M., Kriegel H.-P., Xu X.: “Knowledge Discovery in Large Spatial Databases: Focusing Techniques for Efficient Class Identification”, Proc. 4th Int. Symp. on Large Spatial Databases, Portland, ME, 1995, in: Lecture Notes in Computer Science, Vol. 951, Springer, 1995, pp. 67-82.


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