Abstract
This paper proposes an adaptive text binarization algorithm based on multi-layers to improve the binarization performance of scanned card images. It combines gray information and position information to divide a scanned card image into multiple layers, and proposes a division rate to identify whether to continue layer division. On each text layer, the dual-threshold is applied to eliminate the disturbance of noise and background pattern. Experimental results demonstrate that this approach is robust to various situations and can achieve a good performance in a scanned card image binarization system.
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References
Golder, S.A., Huberman, B.A.: Usage patterns of collaborative tagging systems. J. Inf. Sci. 32(2), 198–208 (2006)
Quintarelli, E.: Folksonomies: power to the people. ISKO Italy-UniMIB Meeting (2005)
Bao, S., Xue, G., Wu, X., Yu, Y., Fei, B., Su, Z.: Optimizing web search using social annotations. In: WWW 2007, pp. 501–510 (2007)
Zhou, D., Bian, J., Zheng, S., Zha, H., Giles, C.L.: Exploring social annotations for information retrieval. In: WWW 2008, pp. 715–724 (2008)
Xu, S., Bao, S., Fei, B., Su, Z., Yu, Y.: Exploring folksonomy for personalized search. In: Porc. of International ACM SIGIR Conference on Research and Development in Information Retrieval, pp. 155–162 (2008)
Conde, J.M., Vallet, D., Castells, P.: Inferring user intent in web search by exploiting social annotations. In: Proc. of International ACM SIGIR Conference on Research and Development in Information Retrieval, pp. 827–828 (2010)
Vallet, D., Cantador, I., Jose, J.M.: Personalizing web search with folksonomy-based user and document profiles. In: Gurrin, C., He, Y., Kazai, G., Kruschwitz, U., Little, S., Roelleke, T., Rüger, S., van Rijsbergen, K. (eds.) ECIR 2010. LNCS, vol. 5993, pp. 420–431. Springer, Heidelberg (2010)
Guo, J., Cheng, X., Xu, G., Shen, H.: A structured approach to query recommendation with social annotation data. In: Proc. of the ACM Conference on Information and Knowledge Management, pp. 619–628 (2010)
Heymann, P., Ramage, D., Garcia-Molina, H.: Social tag prediction. In: SIGIR 2008: Proceedings of the 31st Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, pp. 531–538 (2008)
Lu, Y.-T., Yu, S.-I., Chang, T.-C., Hsu, J.Y.: A content-based method to enhance tag recommendation. In: Proc. of IJCAI 2009, pp. 2064–2069 (2009)
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Liu, C. (2014). Multi-layers Segmentation Based Adaptive Binarization for Text Extraction in Scanned Card Images. In: Huang, DS., Bevilacqua, V., Premaratne, P. (eds) Intelligent Computing Theory. ICIC 2014. Lecture Notes in Computer Science, vol 8588. Springer, Cham. https://doi.org/10.1007/978-3-319-09333-8_40
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DOI: https://doi.org/10.1007/978-3-319-09333-8_40
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-09332-1
Online ISBN: 978-3-319-09333-8
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