DocumentCode :
650193
Title :
Improved Thai text detection from natural scenes
Author :
Woraratpanya, Kuntpong ; Boonchukusol, Pimlak ; Kuroki, Yoshimitsu ; Kato, Yu
Author_Institution :
Fac. of Inf. Technol., King Mongkut´s Inst. of Technol. Ladkrabang, Bangkok, Thailand
fYear :
2013
fDate :
7-8 Oct. 2013
Firstpage :
137
Lastpage :
142
Abstract :
Thai text detection from natural scenes is still a challenging task for language translation applications, since there are many unsolved issues. Furthermore, the existing related works cannot completely detect Thai text. The main reason is that Thai text layout has vowels and tonal marks that differ from other languages. This paper proposes an approach to detect Thai text from natural scenes. The approach consists of two main procedures. (i) Fast boundary clustering algorithm decomposes scene features into multilayers, so that it is faster and easier to analyze Thai text characters. (ii) Modified connected component analysis method is applied to such scene features in order to detect Thai text boundaries. Based on 150 test images with 4,920 characters, the experimental results demonstrate that the proposed approach achieves the high average precision and recall, 0.80 and 0.90.
Keywords :
character recognition; document image processing; feature extraction; language translation; natural language processing; natural scenes; pattern clustering; statistical analysis; text detection; Thai text character recognition; Thai text detection; Thai text layout; boundary clustering algorithm; language translation; modified connected component analysis; natural scene; scene feature decomposition; tonal mark; vowels; Thai text detection; fast boundary clustering; modified connected component analysis; natural scene;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Information Technology and Electrical Engineering (ICITEE), 2013 International Conference on
Conference_Location :
Yogyakarta
Print_ISBN :
978-1-4799-0423-5
Type :
conf
DOI :
10.1109/ICITEED.2013.6676227
Filename :
6676227
Link To Document :
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