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Robust method for the text line detection and splitting of overlapping text in the Latin manuscripts

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The paper presents the modified method of the text lines separation in the handwritten manuscripts. Such an approach is required for the medieval text analysis, where multiple text lines overlap and are written at different angles. The proposed approach consists in dividing the bounding boxes into smaller components based on the points of the character curves intersection. The method considers the askew text lines, producing non-rectangular zones between the neighboring lines.
Twórcy
autor
  • Institute of Radioelectronics, Warsaw University of Technology, Poland
autor
  • Institute of Radioelectronics, Warsaw University of Technology, Poland
Bibliografia
  • [1] L. A. Fletcher and R. Kasturi: A robust algorithm for text string separation from mixed text/graphics images. In IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 10, no. 6, pp. 910-918, 1988.
  • [2] L. Likforman-Sulem and A. Hanimyan and C. Faure: A Hough based algorithm for extracting text lines in handwritten documents. In Proceedings of the Third International Conference on Document Analysis and Recognition, vol. 2, pp. 774-771, 1995.
  • [3] I. S. I. Abuhaiba, S. Datta, and M. J. J. Holt: Line extraction and stroke ordering of text pages. In the Third International Conference on Document Analysis and Recognition, vol. 1, pp. 390-393, 1995.
  • [4] E. Bruzzone and M. C. Coletti : An algorithm for extracting cursive text lines. In Proceedings of the Fifth Internatuional Conference on Document Analysis and Recognition ICDAR ' 99, pp. 749-752, 1999.
  • [5] Yi-Kai Chen and Jhing-Fa Wang: Segmentation of single- or multiple-touching handwritten numeral string using background and foreground analysis. In IEEE Transactions on Pattern Analysis and Machine Intelligence 2000, pp. 1304-1317, 2000.
  • [6] Z. Shi and V. Govindaraju: Line separation for complex document images using fuzzy runlength. In First International Workshop on Document Image Analysis for Libraries, pp. 306-312, 2004.
  • [7] S. Nicolas, T. Paquet, and L. Heutte: Text line segmentation in handwritten document using a production system. In IWFHR-9 2004. Ninth International Workshop on Frontiers in Handwriting Recognition, pp. 245-250, 2004.
  • [8] Z. Shi, S. Setlur, and V. Govindaraju: Text extraction from gray scale historical document images using adaptive local connectivity map. In Eighth International Conference on Document Analysis and Recognition, vol. 2, pp. 794-798, 2005.
  • [9] G. Louloudis, B. Gatos, I. Pratikakis, and K. Halatsis: A block-based Hough transform mapping for text line detection in handwritten documents. In Tenth International Workshop on Frontiers in Handwriting Recognition, 2006.
  • [10] M. Arivazhagan, H. Srinivasan, and S. Srihari: A statistical approach to line segmentation in handwritten documents. In Proc. SPIE 6500, Document Recognition and Retrieval XIV, 65000T, 2007.
  • [11] A. Alaei, P. Nagabhushan, and U. Pal: A new text-line alignment approach based on piece-wise painting algorithm for handwritten documents. In International Conference on Document Analysis and Recognition (ICDAR), pp. 324-328, 2011.
  • [12] Chamchong, R. and Chun Che Fung: A combined method of segmentation for connected hand-written on palm leaf manuscripts. In 2014 IEEE International Conference on Systems, Man and Cybernetics (SMC), pp. 4158-4161, 2014.
  • [13] Gatos, B. and Louloudis, G. and Stamatopoulos, N.: Segmentation of Historical Handwritten Documents into Text Zones and Text Lines. In 14th International Conference on Frontiers in Handwriting Recognition (ICFHR 2014), pp. 464-469, 2014.
  • [14] J. L. Pach, P. Bilski: A Robust Text Line Detection in Complex Handwritten Documents. In The 8th IEEE International Conference on Intelligent Data Acquisition and Advanced Computing Systems: Technology and Applications. (IDAACs 2015), 24-26 Sept. 2015, Warsaw, Poland, pp. 271-275, 2015.
  • [15] Miscellanea theologica 2015. [Online]. Available: http://polona.pl/item/12909419/0/.
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Bibliografia
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bwmeta1.element.baztech-53b30c01-c7af-4bfa-b07a-c8610dcaa00b
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