Abstract
The handwritten digit segmentation is the most important module for handwritten digit recognition, which constitutes a difficult task because of overlapping and / or connected of adjacent digits. To resolve this problem, several segmentation methods have been developed each one having its advantage and disadvantage. In this work, we propose a segmentation approach depending of the configuration link between digits. With the help of a few rules, multiple hypotheses are defined for finding the best segmentation path in order to separate two connected digits. Hence, a verification strategy is proposed in order to generate all possible segmentation-recognition hypotheses. The performance of our strategy is evaluated in terms of correct recognition rates using the confusion matrix.
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Dimauro, G., Impedovo, S., Pirlo, G., Salzo, A.: Automatic Bankcheck processing: A New Engineered System. International Journal of Pattern Recognition and Artificial Intelligence 11(4), 467–504 (1997)
Vellasques, E., Oliveira, L.S., Britto Jr., A.S., Koerich, A.L., Sabourin, R.: Filtering segmentation cuts for digit string recognition. Pattern Recognition 41(10), 3044–3053 (2008)
Congedo, G., Dimauro, G., Impedovo, S., Pirlo, G.: Segmentation of Numeric Strings. In: Proc. of Third Int. Conf. on Document Analysis and Recognition, Canada, pp. 1038–1041. IEEE Computer Society, Montreal (1995)
Jang, B.K., Chin, R.T.: One-pass parallel thinning: Analysis, properties, and quantitative evaluation. IEEE Transactions on Pattern Analysis and Machine Intelligence 14(11), 1129–1140 (1992)
Shridhar, M., Badreldin, A.: Recognition of Isolated and Simply Connected Handwritten Numerals. Journal of Pattern Recognition 19(1), 1–12 (1986)
Ayat, N.E., Cheriet, M., Suen, C.Y.: Un système neuro-flou pour la reconnaissance de montants numériques de chèques arabes. Colloque international francophone sur l’écrit et le document, Montréal, Québec, Canada, pp. 03–07 (2000)
Hussein, K.M., Agarwal, A., Gupta, A., Wang, P.S.P.: A knowledge-based algorithm for enhanced recognition of handwritten courtesy amounts. Pattern Recognition 32, 305–316 (1999)
Oliveira, L.S., Sabourin, R., Bortolozzi, F., Suen, C.Y.: A modular system to recognize numerical amounts on Brazilian bank cheques. In: Proc. of 6th International Conference on Document Analysis and Recognition (ICDAR), Seattle, USA, pp. 389–394. IEEE Computer Society, Los Alamitos (2001)
Fujisawa, H., Nakano, Y., Kurino, K.: Segmentation Methods for Character Recognition: From Segmentation to Document Structure Analysis. Proceedings of the IEEE 80(7), 21–28, 1079–1091 (1996)
Grother. P.J.: NIST Special Database 19; Handprinted Forms and Characters Database. National Institute of Standards and Technology, NIST (1995)
Schölkopf, B., Burges, C., Vapnik, V.: Extracting support data for a given task. In: KDD 1995, pp. 252–257 (1995)
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Gattal, A., Chibani, Y. (2011). Segmentation Strategy of Handwritten Connected Digits (SSHCD). In: Maino, G., Foresti, G.L. (eds) Image Analysis and Processing – ICIAP 2011. ICIAP 2011. Lecture Notes in Computer Science, vol 6979. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-24088-1_26
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DOI: https://doi.org/10.1007/978-3-642-24088-1_26
Publisher Name: Springer, Berlin, Heidelberg
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