Abstract
India is a culturally diverse population having 13 official scripts and 23 official languages. To retrieve information from any documents e.g. ancient, medieval, epigraphs, palm leaf manuscript, and even unregulated document formats written in multi-script/languages requires an optical character recognition system. To develop the efficient and precise multi-script OCR system must require script identification. Due to the script identification context retrieval and accuracy of OCR system is enhanced. This paper presents a review on unconstrained handwritten Indian scripts identification by using various feature extractions method and classifier designs by various researchers.
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
Pal U, Chaudhuri BB (2004) Indian script character recognition: a survey. Pattern Recogn Soc. https://doi.org/10.1016/j.patcog.2004.02.003
Ghosh D, Dube T, Shivaprasad AP (2010) Script recognition—a review. In: IEEE transactions on pattern analysis and machine intelligence
Pal U, Sharma N, Wakabayashi T, Kimura F (2007) Off-line handwritten character recognition of devnagari script. In: Ninth international conference on document analysis and recognition, ICDAR
Hochberg J, Bowers K, Cannon M, Kelly P (1999) Script and language identification for handwritten document images. Int J Doc Anal Recogn (IJDAR) 2:45–52
Singhal V, Ghosh D, Navin N (2003) Script based classification of handwritten text documents in a multi-lingual environment. In: Proceedings of the intel workshop research issues in data engineering multi-lingual information management
Roy K, Baner A Pal U (2004) A system for word-wise handwritten script identification for indian postal automation. In: IEEE India Annual Conference (INDlCON-2004)
Namboodiri AM, Jain AK (2004) Online Handwritten script recognition. IEEE Trans
Rajput GG, Anita HB (2010) Handwritten script recognition using DCT and wavelet features at block level. Int J Comput Appl (IJCA)
Hangarge M, Dhandra BV (2010) Offline handwritten script identification in document images. Int J Comput Appl 4(6):975–8887
Obaidullah SM, Das SK, Roy K (2013) A system for handwritten script identification from indian document. J Pattern Recogn Res 1–12
Pardeshi R, Chaudhuri BB, Hangarge M, Santosh KC (2014) Automatic handwritten indian scripts identification. In: 14th international conference on frontiers in handwriting recognition
Rajput GG, Ummapure SB (2017) Script identification from handwritten documents using SIFT. In: IEEE international conference on power, control, signals and instrumentation engineering (ICPCSI-2017)
Chanda S, Pal U (2018) English, Devnagari and Urdu text identification. In: Proceedings of the international conference on cognition and recognition
Rojatkat DV, Chinchkhede KD, Sarate GG (2013) Design and analysis of LRTB feature based classifier applied to handwritten devnagari characters: a neural network approach. Int Conf Adv Comput Commun Informat (ICACCI)
Joshi GD, Garg S, Sivaswamy J (2006) Script identification from indian documents. Springer, Berlin, Heidelberg (2006)
Gopakumar R, Subba Reddy NV, Makkithaya K, Acharya DU (2010) Script identification from multilingual indian documents using structural features. J Comput 2
Directorate of Government Printing and Stationary, Mumbai. https://www.dgps.maharashtra.gov.in
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2020 Springer Nature Singapore Pte Ltd.
About this paper
Cite this paper
Ganorkar, L.P., Rojatkar, D.V. (2020). A Review on Handwritten Indian Script Identification. In: Kumar, A., Paprzycki, M., Gunjan, V. (eds) ICDSMLA 2019. Lecture Notes in Electrical Engineering, vol 601. Springer, Singapore. https://doi.org/10.1007/978-981-15-1420-3_14
Download citation
DOI: https://doi.org/10.1007/978-981-15-1420-3_14
Published:
Publisher Name: Springer, Singapore
Print ISBN: 978-981-15-1419-7
Online ISBN: 978-981-15-1420-3
eBook Packages: Intelligent Technologies and RoboticsIntelligent Technologies and Robotics (R0)