Abstract
Text line segmentation of historical document is a challenging task in the field of document image analysis due to the presence of narrow spacing between the text lines, overlapping of characters and touching characters. Initially, the document image is preprocessed by means of binarization and thinning. Components are then labeled with the help of connected component labeling method. Finally text lines are localized with the help of projection profile and search for the foreground pixel in the neighborhood to assign characters to their respective text lines. Experimentation is carried on the historical Hoysala Kannada scripts and encouraging results are obtained.
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Acknowledgements
The authors would like to thank Prof. Manjunath M., Head of the department, Prasararanga, University of Mysore for helping us in creating the data base and analyzing them.
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Vishwas, H.S., Thomas, B.A., Naveena, C. (2018). Text Line Segmentation of Unconstrained Handwritten Kannada Historical Script Documents. In: Guru, D., Vasudev, T., Chethan, H., Kumar, Y. (eds) Proceedings of International Conference on Cognition and Recognition . Lecture Notes in Networks and Systems, vol 14. Springer, Singapore. https://doi.org/10.1007/978-981-10-5146-3_23
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DOI: https://doi.org/10.1007/978-981-10-5146-3_23
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