Abstract
Text line segmentation in handwritten documents is a very challenging task because in handwritten documents curved text lines appear frequently. In this paper, we have implemented a general line segmentation approach for handwritten documents with various languages. A novel connectivity strength parameter is used for deciding the groups of the components which belongs to the same line. oversegmentation is also removed with the help of depth first search approach and iterative use of the CSF. We have implemented and tested this approach with English, Hindi and Urdu text images taken from benchmark database and find that it is a language adaptive approach which provide encouraged results. The average accuracy of the proposed technique is 97.30%.
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References
Ouwayed, N., Belaid, A.: A general approach for multi-oriented text line extraction of handwritten documents. IJDAR 15(4), 297–314 (2012)
Kumar, J., et al.: Handwritten Arabic text line segmentation using affinity propagation. In: DAS 2010, pp. 135–142 (2010)
Papavassiliou, V., et al.: Handwritten document image segmentation into text lines and words. Pattern Recognition 43, 369–377 (2010)
Marti, U., Bunke, H.: The IAM-database: An English Sentence Database for Off-line Handwriting Recognition. Int. Journal on Document Analysis and Recognition, IJDAR 5, 39–46 (2002)
Likforman Sulem, L., Zahour, A., Taconet, B.: Text line segmentation of historical documents: A survey. IJDAR 9, 123–138 (2007)
Likforman-Sulem, L., Hanimyan, A., Faure, C.: A Hough based algorithm for extracting text lines in handwritten documents. In: Proc. 3rd Int. Conf. on Document Analysis and Recognition, pp. 774–777 (1995)
Zamora-Martinez, F., Castro-Bleda, M.J., Espaa-Boquera, S., Gorbe-Moya, J.: Unconstrained offline handwriting recognition using connectionist character N-grams. In: The 2010 International Joint Conference on Neural Networks (IJCNN), July 18-23, pp. 1–7 (2010)
Yin, F., Liu, C.-L.: Handwritten Chinese text line segmentation by clustering with distance metric learning. Pattern Recognition (Elsevier) 42(12), 3146–3157 (2009)
Kumar, M., Jindal, M.K., Sharma, R.K.: K-nearest neighbour Based offline Handwritten Gurumukhi Character Recognition. In: International IEEE Conference on Image Information Processing (ICHP 2011), vol. 1, pp. 7–11 (2011)
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Panwar, S., Nain, N., Saxena, S., Gupta, P.C. (2013). Language Adaptive Methodology for Handwritten Text Line Segmentation. In: Wilson, R., Hancock, E., Bors, A., Smith, W. (eds) Computer Analysis of Images and Patterns. CAIP 2013. Lecture Notes in Computer Science, vol 8047. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-40261-6_41
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DOI: https://doi.org/10.1007/978-3-642-40261-6_41
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