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Hand Written Digit Recognition by Multiple Classifier Fusion based on Decision Templates Approach

Authors: Reza Ebrahimpour, Samaneh Hamedi


Classifier fusion may generate more accurate classification than each of the basic classifiers. Fusion is often based on fixed combination rules like the product, average etc. This paper presents decision templates as classifier fusion method for the recognition of the handwritten English and Farsi numerals (1-9). The process involves extracting a feature vector on well-known image databases. The extracted feature vector is fed to multiple classifier fusion. A set of experiments were conducted to compare decision templates (DTs) with some combination rules. Results from decision templates conclude 97.99% and 97.28% for Farsi and English handwritten digits.

Keywords: Decision templates, multi-layer perceptron, characteristics Loci, principle component analysis (PCA).

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[1] S. Impedovo, P. Wang, and H. Bunke, editors, "Automatic Bankcheck Processing," World Scientific, Singapore, 1997.
[2] Nadal, C. Legault, R. Suen and C.Y, "Complementary Algorithms for Recognition of totally Unconstrained Handwritten Numerals," in Proc. 10th Int. Conf. Pattern Recognition, 1990, vol. 1, pp. 434-449.
[3] CL Liu, K Nakashima, H Sako and H. Fujisawa, "Benchmarking of stateof- the-art techniques," Pattern Recognition, vol. 36, no 10, pp. 2271- 2285, Oct. 2003.
[4] M. Shi, Y. Fujisawa, T. Wakabayashi and F. Kimura, "Handwritten numeral recognition using gradient and curvature of gray scale image," Pattern Recognition, vol. 35, no. 10, pp. 2051-2059, Oct 2002.
[5] LN. Teow and KF. Loe, "Robust vision-based features and classification schemes for off-line handwritten digit recognition," Pattern Recognition, vol. 35, no. 11, pp. 2355-2364, Nov. 2002.
[6] K. Cheung, D. Yeung and RT. Chin, "A Bayesian framework for deformable pattern recognition with application to handwritten character recognition," IEEE Trans PatternAnalMach Intell, vol. 20, no. 12, pp. 382-1388, Dec. 1998.
[7] IJ . Tsang, IR. Tsang and DV Dyck, "Handwritten character recognition based on moment features derived from image partition," in Int. Conf. image processing 1998, vol. 2, pp 939-942.
[8] H. Soltanzadeh and M. Rahmati, "Recognition of Persian handwritten digits using image profiles of multiple orientations," Pattern Recognition Lett, vol. 25, no. 14, pp. 1569-1576, Oct.2004.
[9] FN. Said, RA. Yacoub and CY Suen, "Recognition of English and Arabic numerals using a dynamic number of hidden neurons" in Proc. 5th Int Conf. document analysis and recognition, 1999, pp 237-240
[10] J. Sadri, CY. Suen, and TD. Bui, "Application of support vector machines for recognition of handwritten Arabic/Persian digits," in Proc. 2th Iranian Conf. machine vision and image procesing, 2003, vol. 1,pp 300-307.
[11] J. Kittler and F. Roli, "Multiple Classifier Systems," in Proc Int Workshop on Multiple Classifieer Systems, 2000, Springer.
[12] C. Suen and L. Lam, "Multiple classifier combination methodologies for different output level," in Proc Workshop. Multiple Classifier Systems, 2000, pp.52-66.
[13] R. Duin and D. Tax, "Experiments with classifier combination rules," in Proc Workshop. Multiple Classifier Systems, 2000, pp.16-29.
[14] F. alimoglu and E. Alpaydin, "Combining Multiple Representation for Pen-based Hand written Digit Recognition," in Proc. 4th Int Conf. document analysis and recognition, 1997, vol. 2, pp 637-640.
[15] K. Tumer and J. Ghosh, "Error correlation and error reduction in ensemble classifiers," Connect Sc, vol. 8, no. 8, pp. 385-404, 1996.
[16] Gunes, M. Menard, P. Loonis and S. Renaud, "Combination, Cooperation and Selection of Classifiers: a state of the art," Pattern Recognition, vol. 17, no. 8, pp. 1303-1324, 2003.
[17] LI. Kuncheva, M. Skurichina and R.P.W. Duin, "An experimental Study on diversity for bagging and boosting with linear classifiers," Information Fusion, vol. 3, no. 4, pp.245-258, Dec. 2002.
[18] LI. Kuncheva, JC. Bezdek and RP.W. Duin," Decision templates for multiple classifier fusion an experimental comparison," Pattern Recognition, vol. 34, no. 2, pp. 299-314, 2001.
[19] J. Kittler, A. Hojjatoleslami and T. Windeatt, "Weighting Factors in Multiple Expert Fusion," in Proc. Conf. British Machine Vision, 1997, pp. 42-50.
[20] T. Windeatt, R. Ghaderi, "Dynamic Weighting Factors for Decision Combining," in Proc. of IEE Int. Conf. Data Fusion, Great Malvern, UK1998, pp. 123-130.
[21] H. khosravi and E. Kabir, "Introducing a very large dataset of handwritten Farsi digits and a study on their varieties," Pattern Recognition letters, vol. 28, no. 10, pp. 1133-1141, July. 2007.
[22] C. J. Merz, P. M. Murphy, UCI Repository of Machine Learning Databases 1998, http://www.ics
[23] LI. Kuncheva, RK. Kounchev, RZ. Zlatev, "Aggregation of multiple classification decisions by fuzzy templates", in Proc. 3th. European Congres on Intelligent Technologies and Soft Computing, Germany, August 1995, pp. 1470-1474.
[24] ID. Trier and AK. Jain, "Feature Extraction Methods for Character Recognition- A Survey," Pattern Recognition, vol. 29, no. 4, pp. 641- 662, April. 1996.
[25] H. Takahashi, "A Neural Net OCR using geometrical and zonal pattern features," in Proc. 1th. Conf. Document Analysis and Recognition, 1991, pp. 821-828.
[26] L.O. Jimenez, A. Morales-Morell and A. Creus, "Classification of Hyperdimensional Data Based on Feature and Decision Fusion Approachs Using Projection Pursuit, Majority Voting, and Neural Networks," IEEE Trans. on Geoscience and Remote Sensing, vol. 37, no. 3, May 1999.
[27] Y. Li, "Reforming the theory of invariant moments for Pattern recognition," Pattern Recognition Letters, vol. 25, no. 7, pp.723-730, July. 1992.
[28] H.A. Glucksman, "Multicategory of Patterns Represented by High-Order Vectors of Multilevel Measurement," IEEE Transaction Computer, vol. C-20, no. 12, pp. 1593-1598, Dec. 1997.
[29] Sh. Shahreza, M.H. Khotanzad, A. ,"Recognition Letterpress Works Independent of Size and Displacement with Zernike Moments and Neural Networks", in Proc. 2th Iranian Conf of Electrical Engineering,1994, Trbiat modares Univ, vol. 5, pp. 417-424.
[30] K. Azmi, R. Kabir and E. Badi, "Recognition Printed Letters wit Zonong Features," Iran Computer Group, vol. 1, pp. 29-37, 2003.
[31] S.H. Nabavikahrizi, R. Ebrahimpour and E. Kabir, "Application of Combining classifiers for Recognition of Farsi handwritten digits," in Proc. 3th Iranian Conf. Machine vision and image processing, 2004, vol. 1, pp 115-119.
[32] Gorban, B. Kegl, D. Wunsch and A. Zinovyev (Eds.), Principal Manifolds for Data Visualization and Dimension Reduction, LNCSE 58, Springer, Berlin - Heidelberg - New York, 2007. ISBN 978- 3 540- 73749- 0