Abstract
Online handwriting recognition refers to machine recognition of handwriting captured in the form of pen trajectories. This paper describes a trainable online handwriting recognition system for Malayalam using elastic matching technique. Each character/stroke is subjected to a feature extraction procedure. The extracted features forms input to a nearest neighborhood classifier which returns the label having the minimum distance. The recognized characters are assigned their corresponding Unicode code points and are displayed using appropriate fonts. With a database containing 8389 handwritten samples, we get an average word recognition rate of 82%.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Niels, R.: Dynamic Time Warping: An Intuitive Way of Handwriting Recognition? Master’s thesis, Radboud University Nijmegen (2004), http://dtw.noviomagum.com/
Husain, S.A., Sajjad, A., Anwar, F.: Online Urdu Character Recognition System. In: MVA 2007 IAPR Conference on Machine Vision Applications, Tokyo, Japan, pp. 98–101 (2007)
Niels, R., Vuurpijl, L.: Dynamic Time Warping Applied to Tamil Character Recognition. In: Proceedings of 8th ICDAR, pp. 730–734. IEEE, Seoul (2005)
Swethalakshmi, H., Jayaram, A., Chakraborty, V.S., Sekhar, C.C.: Online Handwritten Character Recognition of Devanagari and Telugu Characters using Support Vector Machines. In: Proc. 10th IWFHR, pp. 367–372 (2006)
Raghavendra, B.S., Narayanan, C.K., Sita, G., Ramakrishnan, A.G., Sriganesh, M.: Prototype Learning Methods for Online Handwriting Recognition. In: 8th ICDAR 2005, Seoul, Korea, August 29-September 1, pp. 287–291 (2005)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2011 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Ravindra Kumar, R., Sulochana, K.G., Indhu, T.R. (2011). Online Handwriting Recognition for Malayalam Script. In: Singh, C., Singh Lehal, G., Sengupta, J., Sharma, D.V., Goyal, V. (eds) Information Systems for Indian Languages. ICISIL 2011. Communications in Computer and Information Science, vol 139. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-19403-0_32
Download citation
DOI: https://doi.org/10.1007/978-3-642-19403-0_32
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-19402-3
Online ISBN: 978-3-642-19403-0
eBook Packages: Computer ScienceComputer Science (R0)