Abstract
In this paper, we propose a new approach on segmentation and recognition of off-line unconstrained Arabic handwritten numerals, which failed to be segmented with connected component analysis. In our approach, the touching numerals are automatically segmented when a set of parameters is chosen. Models with different sets of parameters for each numeral pair are designed for recognition. Each image in each model is recognized as an isolated numeral. After normalizing and binarizing the images, gradient features are extracted and recognized using SVMs. Finally, a post-processing is proposed by based on the optimal combinations of the recognition probabilities for each model. Experiments were conducted on the CENPARMI Arabic, Dari, and Urdu touching numeral pair databases [1,12].
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References
Alamri, H., Sadri, J., Nobile, N., Suen, C.: A Novel Comprehensive Database for Arabic Off-Line Handwriting Recognition. In: 11th International Conference on Frontiers in Handwriting Recognition, Montreal, pp. 664–669 (2008)
Al-Omari, F.A., Al-Jarrah, O.: Handwritten Indian numerals recognition system using probabilistic neural networks. Advanced Engineering Informatics 18, 9–16 (2004)
Awaidah, S.M., Mahmoud, S.A.: A multiple feature/resolution scheme to Arabic (Indian) numerals recognition using hidden Markov models. Signal Processing 89, 1176–1184 (2009)
Chang, C.-C., Lin, C.-J.: LIBSVM: a library for support vector machines (2001), http://www.csie.ntu.edu.tw/~cjlin/libsvm
Das, D., Yasmin, R.: Segmentation and Recognition of Unconstrained Bangla Handwritten Numeral. Asian Journal of Information Technology 5(2), 155–159 (2006)
Harifi, A., Aghagolzade, A.: A New Pattern for Handwritten Persian/Arabic Digit Recognition. International Journal of Information Technology 1(4), 293–296 (2004)
Liu, C.L., Sako, H., Fujisawa, H.: Effects of Classifier Structure and Training Regimes on Integrated Segmentation and Recognition of Handwritten Numerals Strings. IEEE Transactions on Pattern Analysis and Machine Intelligence, PAMI 26(11), 1395–1407 (2004)
Lorigo, L., Govindaraju, V.: Offline Arabic handwriting recognition: a survey. IEEE Transactions on Pattern Analysis and Machine Intelligence 28, 712–724 (2006)
Oliveira, L.S., Sabourin, R., Bortolozzi, F., Suen, C.Y.: Automatic Segmentation of Handwritten Numerical Strings: A Recognition and Verification Strategy. IEEE Transactions on Pattern Analysis and Machine Intelligence 24(11), 1438–1454 (2002)
Plamondon, R., Srihari, S.N.: On-line and Off-line Handwriting Recognition: A Comprehensive Survey. IEEE Transaction on Pattern Analysis and Machine Intelligence 22(1), 63–84 (2000)
Sadri, J., Suen, C.Y., Bui, T.D.: Automatic Segmentation of Unconstrained Handwritten Numeral Strings. In: International Workshop on Frontiers in Handwriting Recognition (IWFHR), Tokyo, pp. 317–322 (2004)
Shah, M.I., Sadri, J., Nobile, N., Suen, C.: A New Multipurpose Comprehensive Database for Handwritten Dari Recognition. In: 11th International Conference on Frontiers in Handwriting Recognition, Montreal, pp. 635–640 (2008)
Shi, M., Fujisawa, Y., Wakabayashi, T., Kimura, F.: Handwritten numeral recognition using gradient and curvature of gray scale image. Pattern Recognition 35(10), 2051–2059 (2002)
Vapnik, V., Lerner, A.: Pattern recognition using generalized portrait method. Automation and Remote Control 24, 774–780 (1963)
Wang, Y., Liu, X., Jia, Y.: A holistic approach to handwritten numeral pair recognition based on generative models of numeral pairs. In: 11th International Conference on Frontiers in Handwriting Recognition, Montreal, pp. 54–58 (2008)
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Alamri, H., He, C.L., Suen, C.Y. (2009). A New Approach for Segmentation and Recognition of Arabic Handwritten Touching Numeral Pairs. In: Jiang, X., Petkov, N. (eds) Computer Analysis of Images and Patterns. CAIP 2009. Lecture Notes in Computer Science, vol 5702. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-03767-2_20
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DOI: https://doi.org/10.1007/978-3-642-03767-2_20
Publisher Name: Springer, Berlin, Heidelberg
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