DocumentCode :
2503790
Title :
Comparing Several Techniques for Offline Recognition of Printed Mathematical Symbols
Author :
Álvaro, Francisco ; Sánchez, Joan Andreu
Author_Institution :
Inst. Tecnol. de Inf., Univ. Politec. de Valencia, Valencia, Spain
fYear :
2010
fDate :
23-26 Aug. 2010
Firstpage :
1953
Lastpage :
1956
Abstract :
Automatic recognition of printed mathematical symbols is a fundamental problem for recognition of mathematical expressions. Several classification techniques has been previously used, but there are very few works that compare different classification techniques on the same database and with the same experimental conditions. In this work we have tested classical and novelty classification techniques for mathematical symbol recognition on two databases.
Keywords :
character recognition; image classification; mathematics computing; visual databases; automatic recognition; mathematical expression recognition; mathematical symbol recognition; offline recognition; printed mathematical symbols; Databases; Hidden Markov models; Kernel; Pattern recognition; Prototypes; Support vector machines; Training; Mathematical symbol classification; hidden Markov models; weighted nearest neighbour;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Pattern Recognition (ICPR), 2010 20th International Conference on
Conference_Location :
Istanbul
ISSN :
1051-4651
Print_ISBN :
978-1-4244-7542-1
Type :
conf
DOI :
10.1109/ICPR.2010.481
Filename :
5597241
Link To Document :
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