Abstract
Skew corrected text lines in multi-oriented handwritten documents often contain words that are not properly aligned. Most segmentation algorithms fail to correctly segment skewed words into constituent characters. So, skew correction of words in a text line is as important as skew correction of a text line in a document. In the present work, we propose a method that uses linear curve fitting for estimating and correcting skew present in handwritten words. This method efficiently detects and corrects skew in four Indian languages, namely Bangla, Hindi, Marathi and Panjabi. The proposed method is able to handle skewed word images to an extent of \(\pm {50^{\circ }}\) and provides accurate result even when the \(m\bar{a}tr\bar{a}\) is discontinuous. We have compared our method with existing ones to show the efficacy of the proposed method.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
References
Shi, Z., Govindraju, V.: Skew Detection for Complex Document Images Using Fuzzy Runlength. In: Proceedings of the International Conference on Document Analysis and Recognition, pp. 715–719, (2003)
Srihari, S.N., Govindraju, V.: Analysis of textual image using the Hough transform. Machine Vision Applications, vol. 2, pp. 141–153, (1989)
Chin, A.H.W., Jennings, A.: Skew detection in handwritten scripts. In: Speech and Image Technologies for computation and Telecommunications, pp. 319–322, (1997)
Postl, W.: Detection of linear oblique structures and skew scan in digitized documents. In: Proceedings of the International Conference on Pattern Recognition, pp. 687–689, (1986)
Sarfraz, M., Zidouri, A., Shahab, S.A.: A novel approach for skew estimation of document images in OCR system. In: Proceedings of the International Conference on Computer Graphics, Imaging and Vision: New Trends, pp. 175–180, (2005)
Bagdanov, A., Kanai J.: Projection profile based Skew Estimation Algorithm for JBIG Compressed Images. In: Proceedings of the International Conference on Document Analysis and Recognition, pp. 401–405, (1997)
Bag, S., Bhowmick, P., Harit, G., Biswas, A.: Character segmentation of handwritten Bangla text by vertex characterization of isothetic covers. In: Proceedings of the National Conference on Computer Vision, Pattern Recognition, Image Processing and Graphics, pp. 21–24, (2011)
Bag, S., Krishna, A.: Character Segmentation of Hindi Unconstrained Handwritten Words. In: Proceedings of the International Workshop on Combinatorial Image Analysis, pp. 247–260, (2015)
Bhowmik, T.K., Roy, A., Roy, U.: Character segmentation for handwritten Bangla words using artificial neural network. In: Proceedings of the IAPR TC3 NNLDAR, (2005)
Roy, A., Bhowmik, T.K., Parui, S.K., Roy, U.: A novel approach to skew detection and character segmentation for handwritten Bangla words. In: Digital Image Computing: Techniques and Applications, pp. 30–30, (2005)
Malakar, S., Seraogi, B., Sarkar, R., Das, N., Basu, S., Nasipuri, M.: Two-stage skew correction of handwritten Bangla document images. In: Proceedings of the International Conference on Emerging Applications of Information Technology, pp. 303–306, (2012)
Otsu, N.: A threshold selection method from Gray level histogram. IEEE Transaction on System, Man, Cybernetics, vol. 19, pp. 62–66, (1978)
Rosenfeld, A., Kak, A.: Digital picture processing, \(2^{nd}\) Edition, vol. 1 and 2, Academic press, New York, (1982)
Bhattacharya, U., Shridhar, M., Parui, S.K., Sen, P.K., Chaudhuri, B.B.: Offline recognition of handwritten Bangla characters: an efficient two-stage approach. Pattern Analysis and Applications, vol. 15, no. 4, pp. 445–458, (2012)
Basu, S., Chaudhury, C., Kundu, M., Nasipuri, M., Basu, D.K.: Text line extraction from multi skewed handwritten documents. Pattern Recognition, vol. 40, no. 6, pp. 1825–1839, (2007)
Das, N., Halder, C., Obaidullah, S.M., Roy, K., Santosh, K.C.: PHDIndic_11: page-level handwritten document image dataset of 11 official Indic scripts for script identification. Multimedia Tools and Applications, pp. 1–36, (2017)
Acknowledgements
The authors wish to thank Deepika Gupta, Junior Research Fellow, Department of Computer Science and Engineering, IIT(ISM), Dhanbad, for collecting, organizing and providing the Marathi data set used in this work.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2018 Springer Nature Singapore Pte Ltd.
About this paper
Cite this paper
Pramanik, R., Bag, S. (2018). Linear Regression-Based Skew Correction of Handwritten Words in Indian Languages. In: Chaudhuri, B., Kankanhalli, M., Raman, B. (eds) Proceedings of 2nd International Conference on Computer Vision & Image Processing . Advances in Intelligent Systems and Computing, vol 704. Springer, Singapore. https://doi.org/10.1007/978-981-10-7898-9_11
Download citation
DOI: https://doi.org/10.1007/978-981-10-7898-9_11
Published:
Publisher Name: Springer, Singapore
Print ISBN: 978-981-10-7897-2
Online ISBN: 978-981-10-7898-9
eBook Packages: EngineeringEngineering (R0)