Abstract
The script is a graphical illustration of thinking of a person. Any script can be considered as texture patterns which have linear, oriented and curvilinear sub-pattern primitives. In this paper, the problem of automatic handwritten script identification is considered as texture analysis problem. This paper presents the significance of the traditional Gabor filters in extracting oriented energy distributions. These are tuned efficiently with 24 channels to extract directional energies of text blocks of each script. K nearest neighbor classifier is employed for discriminating six south Indian scripts based on the standard deviations of Gabor filters response. The comprehensive experimentation is conducted on a data set of 600 text block images. Average tri-script classification accuracy with two fold cross validation is 91.99 %.
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
References
Ghosh D, Dube T, Shivaprasad AP (2009) Script recognition—a review. IEEE Trans Pattern Anal Mach Intell 32(12):2142–2161
Guru DS, Ravikumar M, Harish BS (2012) A review on offline handwritten script identification. In: Proceedings of international journal of computer applications on national conference on advanced computing and communications
Ma H, Doermann D (2003) Gabor filter based multi-class classifier for scanned document images. In: Proceedings of the 7th international conference on document analysis and recognition
Pati PB, SabariRaju S, Pati N, Ramakrishnan AG (2004) Gabor filters for document analysis in indian bilingual documents. In: Proceedings of IEEE, ICISIP, pp 123–126
Chanda S, Srikanta P, Franke K, Umapada P (2009) Two-stage approach for word-wise script identification. In: Proceedings of IEEE 10th international conference on document analysis and recognition, pp 926–930
Rajneesh R, Renu D, Lehal GS (2011) Identification of printed Punjabi words and english numerals using gabor features. World Acad Sci Eng Technol 73:392–395
Rajput GG, Anita HB (2010) Handwritten script recognition using dct and wavelet features at block level. IJCA special issue on recent trends in image processing and pattern recognition, pp 158–163
Hangarge M, Dhandra BV (2010) Offline handwritten script identification in document images. Int J Comput Appl 4(6):6–10
Padama MC, Vijaya PA (2010) Script identification from trilingual documents using profile based features. Int J Comput Sci Appl Techno math Res Found 7(4):16–33
Swamy MD, Rani S, Reddy RK, Govardhan A (2011) Script identification from multilingual Telugu, Hindi and English text documents. Int J Wisdom Based Comput 1(3):79–85
Abirami S, Manjula D (2009) A survey of script identification techniques for multi-script document images. Int J Recent Trends Eng 1(2):246–249
Acknowledgments
This work is carried out under the UGC sponsored minor research project (ref: MRP(S):661/09-10/KAGU013/UGCSWRO dated, 30/11/2009). Authors are grateful to the reviewers for giving their valuable comments. Authors are also grateful to the UGC for providing financial assistance.
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2013 Springer India
About this paper
Cite this paper
Hangarge, M., Mukarambi, G., Dhandra, B.V. (2013). South Indian Handwritten Script Identification at Block Level from Trilingual Script Document Based on Gabor Features. In: Swamy, P., Guru, D. (eds) Multimedia Processing, Communication and Computing Applications. Lecture Notes in Electrical Engineering, vol 213. Springer, New Delhi. https://doi.org/10.1007/978-81-322-1143-3_3
Download citation
DOI: https://doi.org/10.1007/978-81-322-1143-3_3
Published:
Publisher Name: Springer, New Delhi
Print ISBN: 978-81-322-1142-6
Online ISBN: 978-81-322-1143-3
eBook Packages: EngineeringEngineering (R0)