Abstract
India is a Multistate- Multilingual country. Most of the people in India used their state official language and English is treated as a binding language used for form filling or some official work. So there is a need to create a system which will convert the handwritten bilingual document into digitized form. This paper aims at development of reader system for handwritten bilingual (Marathi-English) documents by recognizing words. This facilitates many applications such as Natural language processing, School, Society, Banking, post office and Library automation. The proposed system is divided into two phases. The first phase focuses on recognition of handwritten bilingual words using two different feature extraction methods including combination of structural and statistical method and Histogram of Oriented Gradient Method. K-Nearest Neighbor classifier is used for recognition. This classifier gives 82.85% recognition accuracy using Histogram of Oriented Gradient method. The dataset containing 4390 words collected from more than 100 writers. The second phase focuses on digitization and transliteration of recognized words and conversion of transliterated text into speech, which is useful in the society for visually impaired people.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Balakrishnan, K., et al.: Offline handwritten recognition of Malayalam district name-a holistic approach. arXiv preprint arXiv:1705.00794 (2017)
Belaïd, A., Santosh, K.C., d’Andecy, V.P.: Handwritten and printed text separation in real document. arXiv preprint arXiv:1303.4614 (2013)
Dalal, N., Triggs, B.: Histograms of oriented gradients for human detection. In: 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, CVPR 2005, vol. 1, pp. 886–893. IEEE (2005)
Dhandra, B.V., Hangarge, M.: Morphological reconstruction for word level script identification. Int. J. Comput. Sci. Secur. (IJCSS) 1(1), 41–51 (2007)
Gatos, B., Pratikakis, I., Kesidis, A.L., Perantonis, S.J.: Efficient off-line cursive handwriting word recognition. In: Tenth International Workshop on Frontiers in Handwriting Recognition, Suvisoft (2006)
Kamble, P.M., Hegadi, R.S.: Handwritten Marathi basic character recognition using statistical method (2014)
Sandyal, K.S., Patel, M.S.: Offline handwritten Kannada word recognition. pp. 19–22 (2014)
Manoj Kumar, P., Chandran, S.: Handwritten Malayalam word recognition system using neural networks. Int. J. Eng. Res. Technol. 4, 90–99 (2015)
Obaidullah, S.M., Santosh, K.C., Das, N., Halder, C., Roy, K.: Handwritten Indic script identification in multi-script document images: a survey. Int. J. Pattern Recogn. Artif. Intell. 32(10), 1856012 (2018)
Obaidullah, S.M., Santosh, K.C., Halder, C., Das, N., Roy, K.: Automatic Indic script identification from handwritten documents: page, block, line and word-level approach. Int. J. Mach. Learn. Cybern. 10, 1–20 (2017)
Otsu, N.: A threshold selection method from gray-level histograms. IEEE Trans. Syst. Man Cybern. 9(1), 62–66 (1979)
Pal, U., Chaudhuri, B.B.: Automatic separation of words in multi-lingual multi-script Indian documents. In: ICDAR, p. 576. IEEE (1997)
Patel, M.S., Kumar, R., Linga Reddy, S.C.: Offline Kannada handwritten word recognition using locality preserving projection (LPP) for feature extraction. IJIRSET, 4(7) (2015)
Patel, M.S., Reddy, S.L., Naik, A.J.: An efficient way of handwritten English word recognition. In: Satapathy, S.C., Biswal, B.N., Udgata, S.K., Mandal, J.K. (eds.) Proceedings of the 3rd International Conference on Frontiers of Intelligent Computing: Theory and Applications (FICTA) 2014. AISC, vol. 328, pp. 563–571. Springer, Cham (2015). https://doi.org/10.1007/978-3-319-12012-6_62
Ansari, S., Patil, P.M.: A research survey of Devnagari handwritten word recognition. Int. J. Eng. Res. Technol. 2(10), 1010–1015 (2013)
Plamondon, R., Srihari, S.N.: Online and off-line handwriting recognition: a comprehensive survey. IEEE Trans. Pattern Anal. Mach. Intell. 22(1), 63–84 (2000)
Shaikh, M.A., Dagade, M.R.: Offline recognition of handwritten devanagari words using hidden markov model. IJIRST, 1(11) (2015)
Shaw, B., Parui, S.K., Shridhar, M.: Offline handwritten Devanagari word recognition: a segmentation based approach. In: 2008 19th International Conference on Pattern Recognition, ICPR 2008, pp. 1–4. IEEE (2008)
Singh, B., Mittal, A., Ansari, M.A., Ghosh, D.: Handwritten Devanagari word recognition: a curvelet transform based approach. Int. J. Comput. Sci. Eng. 3(4), 1658–1665 (2011)
Student, R.V.: Off-line handwritten Kannada text recognition using support vector machine using zernike moments. IJCSNS 11(7), 128 (2011)
Zinjore, R.S., Ramteke, R.J., Pathak, V.M.: Segmentation of merged lines and script identification in handwritten bilingual documents. In: Proceedings of the 9th Annual Meeting of the Forum for Information Retrieval Evaluation, pp. 29–32. ACM (2017)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2019 Springer Nature Singapore Pte Ltd.
About this paper
Cite this paper
Zinjore, R.S., Ramteke, R.J. (2019). Reader System for Transliterate Handwritten Bilingual Documents. In: Santosh, K., Hegadi, R. (eds) Recent Trends in Image Processing and Pattern Recognition. RTIP2R 2018. Communications in Computer and Information Science, vol 1037. Springer, Singapore. https://doi.org/10.1007/978-981-13-9187-3_16
Download citation
DOI: https://doi.org/10.1007/978-981-13-9187-3_16
Published:
Publisher Name: Springer, Singapore
Print ISBN: 978-981-13-9186-6
Online ISBN: 978-981-13-9187-3
eBook Packages: Computer ScienceComputer Science (R0)