Multi-Script Line identification from Indian Documents

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Seventh International Conference on Document Analysis and Recognition (ICDAR'03) - Volume 2

Edinburgh, Scotland

August 03-August 06

ISBN: 0-7695-1960-1

	ASCII Text	x
	U. Pal, S. Sinha, B. B. Chaudhuri, "Multi-Script Line identification from Indian Documents," Document Analysis and Recognition, International Conference on, vol. 2, pp. 880, Seventh International Conference on Document Analysis and Recognition (ICDAR'03) - Volume 2, 2003.

	BibTex	x
	@article{ 10.1109/ICDAR.2003.1227786, author = {U. Pal and S. Sinha and B. B. Chaudhuri}, title = {Multi-Script Line identification from Indian Documents}, journal ={Document Analysis and Recognition, International Conference on}, volume = {2}, year = {2003}, isbn = {0-7695-1960-1}, pages = {880}, doi = {http://doi.ieeecomputersociety.org/10.1109/ICDAR.2003.1227786}, publisher = {IEEE Computer Society}, address = {Los Alamitos, CA, USA}, }

	RefWorks Procite/RefMan/Endnote	x
	TY - CONF JO - Document Analysis and Recognition, International Conference on TI - Multi-Script Line identification from Indian Documents SN - 0-7695-1960-1 SP EP A1 - U. Pal, A1 - S. Sinha, A1 - B. B. Chaudhuri, PY - 2003 KW - null VL - 2 JA - Document Analysis and Recognition, International Conference on ER -

U. Pal, Indian Statistical Institute

S. Sinha, Indian Statistical Institute

B. B. Chaudhuri, Indian Statistical Institute

DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/ICDAR.2003.1227786

A document page may contain two or more different scripts. For Optical Character Recognition (OCR) of such a document page, it is necessary to separate different scripts before feeding them to their individual OCR system. In this paper an automatic scheme is presented to identify text lines of different Indian scripts from a document. For the separation task at first the scripts are grouped into a few classes according to script characteristics. Next feature based on water reservoir principle, contour tracing, profile etc. are employed to identify them without any expensive OCR-like algorithms. At present, the system has an overall accuracy of about 97.52%.

Citation:

U. Pal, S. Sinha, B. B. Chaudhuri, "Multi-Script Line identification from Indian Documents," icdar, vol. 2, pp.880, Seventh International Conference on Document Analysis and Recognition (ICDAR'03) - Volume 2, 2003

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