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An Efficient Feature Extraction Algorithm for the Recognition of Handwritten Arabic Digits
In this paper, an efficient structural approach for recognizing on-line handwritten digits is proposed. After reading the digit from the user, the slope is estimated and normalized for adjacent nodes. Based on the changing of signs of the slope values, the primitives are identified and extracted. The names of these primitives are represented by strings, and then a finite state machine, which contains the grammars of the digits, is traced to identify the digit. Finally, if there is any ambiguity, it will be resolved. Experiments showed that this technique is flexible and can achieve high recognition accuracy for the shapes of the digits represented in this work.
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[1] C. C. Tappert, C. Y. Suen, and T. Wakahara, "The state of the art in on-line handwriting recognition", IEEE Trans. On Pattern Analysis and Machine Intelligence, vol 12, no 8, pp. 787-808, 1990.
[2] R. G. Casey and E. Lecolinet, "Strategies in character segmentation: A survey", In Proceedings of International Conference on Document Analysis and Recognition, pp. 1028-1033, 1995.
[3] K. S. Fu, Syntactic Pattern Recognition and Applications, Prentice- Hall, Englewood Cliffs, NJ, 1982.
[4] T. Pavlidis, Structural Pattern Recognition, Springer, New York, 1977.
[5] s. Lucas, E. Vidal, A. Amiri, S. Hanlon, and J.C. Amengual, "A comparison of syntactic and statistical techniqes for off-line OCR", in: R. C. Carrasco, J. Oncina (Eds.), Grammatical Inferrence and Applications (ICGI-94), Springer, Berlin, pp. 168-179, 1994.
[6] Brijesh Verma, "A Contour Code Feature Based Segmentation For Handwriting Recognition". Proceedings of the Seventh International Conference on Document Analysis and Recognition (ICDAR 2003).
[7] Daekeun You and Gyeonghwan Kim, "An approach for locating segmentation points of handwritten digit strings using a neural network", Proceedings of the Seventh International Conference on Document Analysis and Recognition (ICDAR 2003).
[8] Robert T. Olszewski, "Generalized Feature Extraction for Structural Pattern Recognition in TimeSeries Data", PhD thesis, University- Pittsburgh, 2001.
[9] Kam-Fai Chan and Dit-Yan Yeung, "An effecient syntactic approach to structural analysis of on-line handwritten mathematical expressions", Pattern Recognition, vol 33, pp. 375-384, 2000.
[10] Kam-Fai Chan and Dit-Yan Yeung, "Recognizing on-line handwritten alphanumeric characters through flexible structural matching", Pattern Recognition, vol 32, pp. 1099-1114, 1999.
[11] Adnan Amin, "Off-Line Arabic Character Recognition: The State Of The Art", Pattern Recognition, 31(5), 517-530, (1998).
[12] Sven Behnke, Marcus Pfisher, and Raul Rojas, "A Study on the Combination of Classifiers for Handwritten Didit Recognition", Proceedings of Neural Networks in Applications, Third International Workshop (NN'98), Magdeburg, Germany, pp. 39-46, 1998.
[13] Sven Behnke, Raul Rojas, and Marcus Pfister, "Recognition of Handwritten Digits using Structural Information", Proceedings of the International Conference of Nueral Network, Houston TX, vol 3, pp. 1391-1396, 1997.
[14] S. Madhvanath, G. Kim, and V. Govindaraju, "Chaincode Contour Processing for Handwritten Word Recognition", IEEE Trans. On Pattern Analysis and Machine Intelligence, vol 21, no 9, pp. 928 932, 1999.
[15] Robert Schalkoff, Pattern Recognition: Statistical, Structural, and Neural Approaches", John Wiley & Sons Inc. 1992.
[16] Rafael C. Gonzalez and Michael G. Thomason, Syntactic Pattern Recognition: An Introduction, Addison Wesley, Reading, Massachusetts, 1978.
[17] Richard O. Duda, Peter E. Hart, and David E. Stork. Pattern Classification. Wiley, New York, second edition, 2001.
[18] Keinosuke Fukunaga. Introduction to Statistical Pattern Recognition. Academic Press, Boston, second edition, 1990.
[19] Anil K. Jain, Robert P. W. Duin, and Jianchang Mao. Statistical Pattern Recognition: A Review. IEEE Transactions on Pattern Analysis and Machine Intelligence, 22(1):4 -37, January 2000.
[20] Robert T. Olszewski, "Generalized Feature Extraction for Structural Pattern Recognition in TimeSeries Data", PhD. Thesis, 2001, School of Computer Science, Carnegie Mellon University, Pittsburgh, PA 15213.
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