Have a personal or library account? Click to login
Projection–Based Text Line Segmentation with a Variable Threshold Cover

Projection–Based Text Line Segmentation with a Variable Threshold

Open Access
|May 2017

References

  1. Alaei, A., Nagabhushan, P. and Pal, U. (2011). Piece-wise painting technique for line segmentation of unconstrained handwritten text: A specific study with Persian text documents, Pattern Analysis and Applications14(4): 381–394.10.1007/s10044-011-0226-x
  2. Antonacopoulos, A. and Karatzas, D. (2004). Document image analysis for World War II personal records, International Workshop on Document Image Analysis for Libraries, 2004, Palo Alto, CA, USA, pp. 336–341.
  3. Arlot, S. and Celisse, A. (2010). A survey of cross-validation procedures for model selection, Statistics Surveys4: 40–79.10.1214/09-SS054
  4. Basu, S., Chaudhuri, C., Kundu, M., Nasipuri, M. and Basu, D.K. (2007). Text line extraction from multi-skewed handwritten documents, Pattern Recognition40(6): 1825–1839.10.1016/j.patcog.2006.10.002
  5. Bouckaert, R.R. and Frank, E. (2004). Evaluating the Replicability of Significance Tests for Comparing Learning Algorithms, Springer, Berlin/Heidelberg, pp. 3–12.
  6. Brodić, D. (2012). Extended approach to water flow algorithm for text line segmentation, Journal of Computer Science and Technology27(1): 187–194.10.1007/s11390-012-1216-1
  7. Brodić, D. (2015). Text line segmentation with water flow algorithm based on power function, Journal of Electrical Engineering66(3): 132–141.10.2478/jee-2015-0021
  8. Brodić, D. and Milivojević, Z. (2011). A new approach to water flow algorithm for text line segmentation, Journal of Universal Computer Science17(1): 30–47.
  9. Cierniak, R. (2014). An analytical iterative statistical algorithm for image reconstruction from projections, International Journal of Applied Mathematics and Computer Science24(1): 7–17, DOI: 10.2478/amcs-2014-0001.10.2478/amcs-2014-0001
  10. Demšar, J. (2006). Statistical comparisons of classifiers over multiple data sets, The Journal of Machine Learning Research7: 1–30.
  11. Dietterich, T.G. (1998). Approximate statistical tests for comparing supervised classification learning algorithms, Neural Computation10(7): 1895–1923.10.1162/0899766983000171979744903
  12. dos Santos, R.P., Clemente, G.S., Ren, T.I. and Cavalcanti, G. D. (2009). Text line segmentation based on morphology and histogram projection, 10th International Conference on Document Analysis and Recognition, ICDAR’09, Barcelona, Spain, pp. 651–655.
  13. Fabijańska, A., Węgliński, T., Zakrzewski, K. and Nowosławska, E. (2014). Assessment of hydrocephalus in children based on digital image processing and analysis, International Journal of Applied Mathematics and Computer Science24(2): 299–312, DOI: 10.2478/amcs-2014-0022.10.2478/amcs-2014-0022
  14. Ha, J., Haralick, R.M. and Phillips, I.T. (1995). Document page decomposition by the bounding-box project, 3rd International Conference on Document Analysis and Recognition, Montreal, Canada, Vol. 2, pp. 1119–1122.
  15. Holm, S. (1979). A simple sequentially rejective multiple test procedure, Scandinavian Journal of Statistics6(2): 65–70.
  16. Hull, J.J. (1998). Document image skew detection: Survey and annotated bibliography, Series in Machine Perception and Artificial Intelligence29: 40–66.10.1142/9789812797704_0003
  17. ICDAR (2013). Handwriting Segmentation Contest, http://users.iit.demokritos.gr/∼nstam/ICDAR2013HandSegmCont/index.html.
  18. Japkowicz, N. and Shah, M. (2011). Evaluating Learning Algorithms: A Classification Perspective, Cambridge University Press, Cambridge, NY.10.1017/CBO9780511921803
  19. Krstajic, D., Buturovic, L., Leahy, D. and Thomas, S. (2014). Cross-validation pitfalls when selecting and assessing regression and classification models, Journal of Cheminformatics6(1): 10.10.1186/1758-2946-6-10399424624678909
  20. LeBourgeois, F. (1997). Robust multifont OCR system from gray level images, 4th International Conference on Document Analysis and Recognition, 1997, Ulm, Germany, Vol. 1, pp. 1–5.
  21. Likforman-Sulem, L. and Faure, C. (1994). Extracting text lines in handwritten documents by perceptual grouping, in C. Faure et al. (Eds.), Advances in Handwriting and Drawing: A Multidisciplinary Approach, Europia, Paris, pp. 21–38.
  22. Likforman-Sulem, L., Hanimyan, A. and Faure, C. (1995). A Hough based algorithm for extracting text lines in handwritten documents, 3rd International Conference on Document Analysis and Recognition, Montreal, Canada, Vol. 2, pp. 774–777.
  23. Likforman-Sulem, L., Zahour, A. and Taconet, B. (2007). Text line segmentation of historical documents: A survey, International Journal of Document Analysis and Recognition9(2–4): 123–138.10.1007/s10032-006-0023-z
  24. Lim, J.S. (1990). Two-Dimensional Signal and Image Processing, Prentice Hall, Englewood Cliffs, NJ.
  25. Louloudis, G., Gatos, B., Pratikakis, I. and Halatsis, C. (2008). Text line detection in handwritten documents, Pattern Recognition41(12): 3758–3772.10.1016/j.patcog.2008.05.011
  26. Louloudis, G., Gatos, B., Pratikakis, I. and Halatsis, C. (2009). Text line and word segmentation of handwritten documents, Pattern Recognition42(12): 3169–3183.10.1016/j.patcog.2008.12.016
  27. Manmatha, R. and Srimal, N. (1999). Scale space technique for word segmentation in handwritten documents, in M. Nielsen et al. (Eds.), Scale-Space Theories in Computer Vision, Springer, Berlin/Heidelberg, pp. 22–33.10.1007/3-540-48236-9_3
  28. Marti, U.-V. and Bunke, H. (2001a). On the influence of vocabulary size and language models in unconstrained handwritten text recognition, 6th International Conference on Document Analysis and Recognition, Seattle, WA, USA, pp. 260–265.
  29. Marti, U.-V. and Bunke, H. (2001b). Using a statistical language model to improve the performance of an HMM-based cursive handwriting recognition system, International Journal of Pattern Recognition and Artificial Intelligence15(01): 65–90.10.1142/S0218001401000848
  30. Nadeau, C. and Bengio, Y. (2003). Inference for the generalization error, Machine Learning52(3): 239–281.10.1023/A:1024068626366
  31. O’Gorman, L. (1993). The document spectrum for page layout analysis, IEEE Transactions on Pattern Analysis and Machine Intelligence15(11): 1162–1173.10.1109/34.244677
  32. Otsu, N. (1975). A threshold selection method from gray-level histograms, Automatica11(285-296): 23–27.
DOI: https://doi.org/10.1515/amcs-2017-0014 | Journal eISSN: 2083-8492 | Journal ISSN: 1641-876X
Language: English
Page range: 195 - 206
Submitted on: Jan 17, 2016
|
Accepted on: Oct 24, 2016
|
Published on: May 4, 2017
In partnership with: Paradigm Publishing Services
Publication frequency: 4 issues per year

© 2017 Roman Ptak, Bartosz Żygadło, Olgierd Unold, published by University of Zielona Góra
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.