Artificial Neural Network Based Sinhala Character Recognition

被引：1

作者：

Premachandra, H. Waruna H. ^{[1
]}

Premachandra, Chinthaka ^{[2
]}

Kimura, Tomotaka ^{[3
]}

Kawanaka, Hiroharu ^{[4
]}

机构：

[1] Wayamba Univ Srilanka, ICT Ctr, Makadura, Sri Lanka

[2] Shibaura Inst Technol, Dept Elect Engn, Koto Ku, 3-7-5 Toyosu, Tokyo 1358548, Japan

[3] Tokyo Univ Sci, Katsushika Ku, 6-3-1 Niijuku, Tokyo 1258585, Japan

[4] Mie Univ, Grad Sch Engn, 1577 Kurimamachiya Cho, Tsu, Mie 5148507, Japan

来源：

COMPUTER VISION AND GRAPHICS, ICCVG 2016 | 2016年 / 9972卷

关键词：

Character recognition; Sinhala script; Character geometry features; Artificial neural networks;

D O I：

10.1007/978-3-319-46418-3_53

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Sinhala is the main language spoken by the majority of the population of Sri Lanka. There is a clear need for an optical character recognition (OCR) system for the Sinhala language. However, the language contains very similar characters, which makes it very difficult to distinguish them except on feature analysis. The character recognition rates of previous systems proposed for Sinhala character recognition are low, and so further improvement is needed. Consequently, in this paper, we propose a new Sinhala character recognition method that uses character geometry features and artificial neural network (ANN). The results of experiments conducted using various documentary images of the Sinhala language indicate that the proposed method has better character recognition performance than conventional methods.

引用

页码：594 / 603

页数：10

共 15 条

[1]

Aiquan Yuan, 2012, Proceedings of the 10th IAPR International Workshop on Document Analysis Systems (DAS 2012), P125, DOI 10.1109/DAS.2012.61

[2]

[Anonymous], 2012, 2012 IEEE INT C ELEC, DOI DOI 10.1109/EIT.2012.6220772

[3]

De Cao Tran, 2010, Proceedings 2010 12th International Conference on Frontiers in Handwriting Recognition (ICFHR 2010), P65, DOI 10.1109/ICFHR.2010.16

[4]

Fernando HC, 2003, PROC INT CONF DOC, P1262

[5] An Empirical Comparative Study of Online Handwriting Chinese Character Recognition:Simplified v.s. Traditional [J].

Gao, Yan ;

Jin, Lianwen ;

Yang, Weixin .

2013 12TH INTERNATIONAL CONFERENCE ON DOCUMENT ANALYSIS AND RECOGNITION (ICDAR), 2013, :862-866

[6]

Gaurav D. D., 2012, ARXIV12023884

[7]

Hewavitharana S., 2002, IND C COMP VIS GRAPH, P266

[8]

Huang L., 2010, INT C COMP DES APPL

[9]

Karunanayaka M. L. M., 2005, MVA IAPR C MACH VIS

[10]

Kodituwakku S. R., 2010, INT J ENG SCI TECHNO, V2, P6031

← 1 2 →