Please use this identifier to cite or link to this item: http://hdl.handle.net/10553/46146
Title: LBP based line-wise script identification
Authors: Ferrer, Miguel A. 
Morales, Aythami
Pal, Umapada
UNESCO Clasification: 3307 Tecnología electrónica
Keywords: optical character recognition
least squares approximations
support vector machines
document image processing
text detection
Issue Date: 2013
Journal: Proceedings of the International Conference on Document Analysis and Recognition, ICDAR
Conference: 12th International Conference on Document Analysis and Recognition (ICDAR) 
12th International Conference on Document Analysis and Recognition, ICDAR 2013 
Abstract: Script identification is an important step in multi-script document analysis. As different textures present in text portion of a script are the main distinct features of the script, in this paper, we proposed a new algorithm for printed script identification based on texture analysis. Since local patterns is a unifying concept for traditional statistical and structural approaches of texture analysis, here the basic idea is to use the histogram of the local patterns as description of the script stroke directions distribution which is the characteristic of every script. As local pattern, the basic version of the Local Binary Patterns (LBP) and a modified version of the Orientation of the Local Binary Patterns (OLBP) are proposed. A Least Square Support Vector Machine (LS-SVM) is used as identifier. The scheme has been verified on two databases. The first or training database is a database with 200 sheets of 10 different scripts. The scripts font is provided by the Google translator. The second or test database has been obtained by scanning different newspapers and books. It contains 5 common scripts among 10 different scripts of the first database. From the experiment we obtained encouraging results.
URI: http://hdl.handle.net/10553/46146
ISSN: 1520-5363
DOI: 10.1109/ICDAR.2013.81
Source: Proceedings of the International Conference on Document Analysis and Recognition, ICDAR[ISSN 1520-5363] (6628646), p. 369-373
Appears in Collections:Actas de congresos
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