Line Segmentation of Handwritten Text Using Histograms and Tensor Voting

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-xSearch in Google Scholar

Arivazhagan, M., Srinivasan, H. and Srihari, S. (2007). A statistical approach to line segmentation in handwritten documents, Document Recognition and Retrieval XIV65000: 245–255.10.1117/12.704538Search in Google Scholar

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.2006.10.002Search in Google Scholar

Boykov, Y. and Kolmogorov, V. (2004). An experimental comparison of min-cut/max-flow algorithms for energy minimization in vision, IEEE Transactions on Pattern Analysis and Machine Intelligence26(9): 1124–1137.10.1109/TPAMI.2004.6015742889Search in Google Scholar

Brodić, D. (2012). Extended approach to water flow algorithm for text line segmentation, Journal of Computer Science and Technology27(1): 187–194.10.1007/s11390-012-1216-1Search in Google Scholar

Brodić, D. (2015). Text line segmentation with water flow algorithm based on power function, Journal of Electrical Engineering66(3): 132–141.10.2478/jee-2015-0021Search in Google Scholar

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.Search in Google Scholar

Eskenazi, S., Gomez-Kr¨amer, P. and Ogier, J.-M. (2017). A comprehensive survey of mostly textual document segmentation algorithms since 2008, Pattern Recognition64: 1–14.10.1016/j.patcog.2016.10.023Search in Google Scholar

Feldbach, M. and Tönnies, K. (2001). Robust line detection in historical church registers, 23rd DAGM Symposium on Pattern Recognition, Munich, Germany, pp. 140–147.Search in Google Scholar

Franken, E., van Almsick, M., Rongen, P., Florack, L. and ter Haar Romeny, B. (2006). An efficient method for tensor voting using steerable filters, European Conference on Computer Vision, Graz, Austria, pp. 228–240.Search in Google Scholar

Gatos, B., Stamatopoulos, N. and Louloudis, G. (2011). ICDAR 2009 handwriting segmentation contest, International Journal on Document Analysis and Recognition14(1): 25–33.10.1007/s10032-010-0122-8Search in Google Scholar

Han, S., Lee, M.-S. and Medioni, G. (1997). Non-uniform skew estimation by tensor voting, Workshop on Document Image Analysis (DIA’97), San Juan, Puerto Rico, pp. 1–4.Search in Google Scholar

Kennard, D.J. and Barrett, W.A. (2006). Separating lines of text in free-form handwritten historical documents, 2nd International Conference on Document Image Analysis for Libraries (DIAL’06), Lyon, France, pp. 12–23.Search in Google Scholar

LeBourgeois, F. (1997). Robust multifont OCR system from gray level images, Proceedings of the 4th International Conference on Document Analysis and Recognition, Ulm, Germany, Vol. 1, pp. 1–5.Search in Google Scholar

Lee, M.-S. and Medioni, G. (1997). Inferred descriptions in terms of curves, regions and junctions from sparse, noisy binary data, 3rd International Workshop on Visual Form, Capri, Italy, pp. 350–367.Search in Google Scholar

Li, Y., Zheng, Y., Doermann, D. and Jaeger, S. (2008). Script-independent text line segmentation in freestyle handwritten documents, Pattern Analysis and Machine Intelligence, IEEE Transactions on30(8): 1313–1329.10.1109/TPAMI.2007.7079218566488Search in Google Scholar

Likforman-Sulem, L., Hanimyan, A. and Faure, C. (1995). A hough based algorithm for extracting text lines in handwritten documents, Proceedings of the 3rd International Conference on Document Analysis and Recognition, Montreal, Quebec, Canada, Vol. 2, pp. 774–777.Search in Google Scholar

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): 123–138.10.1007/s10032-006-0023-zSearch in Google Scholar

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.2008.05.011Search in Google Scholar

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.2008.12.016Search in Google Scholar

Maggiori, E., Manterola, H.L. and del Fresno, M. (2014). Perceptual grouping by tensor voting: A comparative survey of recent approaches, IET Computer Vision9(2): 259–277.10.1049/iet-cvi.2014.0103Search in Google Scholar

Medioni, G. and Kang, S.B. (2004). Emerging Topics in Computer Vision, Prentice Hall, Upper Saddle River, NJ.Search in Google Scholar

Mordohai, P. and Medioni, G. (2006). Tensor voting: A perceptual organization approach to computer vision and machine learning, Synthesis Lectures on Image, Video, and Multimedia Processing2(1): 1–136.10.2200/S00049ED1V01Y200609IVM008Search in Google Scholar

Naz, S. (2015). Segmentation techniques for recognition of Arabic-like scripts: A comprehensive survey, Springer Journal of Education and Information Technologies21(5): 1225–1241.10.1007/s10639-015-9377-5Search in Google Scholar

Nguyen Dinh, T. and Lee, G.S. (2011). Text line segmentation in handwritten document images using tensor voting, IEICE Transactions on Fundamentals of Electronics, Communications and Computer SciencesE94.A(11): 2434–2441.Search in Google Scholar

Nguyen Dinh, T., Park, J.-H. and Lee, G.-S. (2010). Voting based text line segmentation in handwritten document images, 10th IEEE International Conference on Computer and Information Technology, Bradford, UK, pp. 529–535.Search in Google Scholar

Pach, J.L. and Bilski, P. (2014). Robust method for the text line detection and splitting of overlapping text in the Latin manuscripts, Machine Graphics and Vision23(3–4): 11–22.10.22630/MGV.2014.23.3.2Search in Google Scholar

Papavassiliou, V., Katsouros, V. and Carayannis, G. (2010). A morphological approach for text-line segmentation in handwritten documents, 2010 International Conference on Frontiers in Handwriting Recognition (ICFHR), Kolkata, India, pp. 19–24.Search in Google Scholar

Phillips, I.T. and Chhabra, A.K. (1999). Empirical performance evaluation of graphics recognition systems, IEEE Transactions on Pattern Analysis and Machine Intelligence21(9): 849–870.10.1109/34.790427Search in Google Scholar

Ptak, R., Żygadło, B. and Unold, O. (2017). Projection-based text line segmentation with a variable threshold, International Journal of Applied Mathematics and Computer Science27(1): 195–206, DOI: 10.1515/amcs-2017-0014.10.1515/amcs-2017-0014Search in Google Scholar

Pu, Y. and Shi, Z. (1999). A natural learning algorithm based on hough transform for text lines extraction in handwritten documents, Advances in Handwriting Recognition34: 141–150.10.1142/9789812797650_0014Search in Google Scholar

Razak, Z., Zulkiflee, K., Idris, M.Y.I., Tamil, E.M., Noorzaily, M., Noor, M., Salleh, R., Yaakob, M., Yusof, Z.M. and Yaacob, M. (2008). Off-line handwriting text line segmentation: A review, International Journal of Computer Science and Network Security8(7): 12–20.10.3923/itj.2009.971.981Search in Google Scholar

Sarkar, R., Malakar, S., Das, N., Basu, S., Kundu, M. and Nasipuri, M. (2011). Word extraction and character segmentation from text lines of unconstrained handwritten Bangla document images, Journal of Intelligent Systems20(3): 227–260.10.1515/jisys.2011.013Search in Google Scholar

Vo, Q.N., Kim, S.H., Yang, H.J. and Lee, G.S. (2018). Text line segmentation using a fully convolutional network in handwritten document images, IET Image Processing12(3): 438–446.10.1049/iet-ipr.2017.0083Search in Google Scholar

Wong, K.Y., Casey, R.G. and Wahl, F.M. (1982). Document analysis system, IBM Journal of Research and Development26(6): 647–656.10.1147/rd.266.0647Search in Google Scholar

Wu, J.-C., Hsieh, J.-W. and Chen, Y.-S. (2008). Morphology-based text line extraction, Machine Vision and Applications19(3): 195–207.10.1007/s00138-007-0092-0Search in Google Scholar

Wu, T.-P., Yeung, S.-K., Jia, J., Tang, C.-K. and Medioni, G. (2012). A closed-form solution to tensor voting: Theory and applications, IEEE Transactions on Pattern Analysis and Machine Intelligence34(8): 1482–1495.10.1109/TPAMI.2011.25022184257Search in Google Scholar

Zhang, C. and Lee, G.S. (2011). Text line segmentation in Chinese handwritten text images, 17th Korea–Japan Joint Workshop on Frontiers of Computer Vision (FCV), Ulsan, South Korea, pp. 253–255.Search in Google Scholar