Abstract
In this paper, a statistical decision method for automatic classification of spatial relationships between each adjacent pair is proposed. Each pair is composed of mathematical symbols and/or alphabetical characters. Special treatment of mathematical symbols with variable size is important. This classification is important to recognize an accurate structure analysis module of math OCR. Experimental results on a very large database showed that the proposed method worked well with an accuracy of 99.57% by two important geometric feature relative size and relative position.
| Original language | English |
|---|---|
| Title of host publication | ICDAR2009 - 10th International Conference on Document Analysis and Recognition |
| Pages | 1350-1354 |
| Number of pages | 5 |
| DOIs | |
| Publication status | Published - Dec 10 2009 |
| Event | ICDAR2009 - 10th International Conference on Document Analysis and Recognition - Barcelona, Spain Duration: Jul 26 2009 → Jul 29 2009 |
Publication series
| Name | Proceedings of the International Conference on Document Analysis and Recognition, ICDAR |
|---|---|
| ISSN (Print) | 1520-5363 |
Other
| Other | ICDAR2009 - 10th International Conference on Document Analysis and Recognition |
|---|---|
| Country | Spain |
| City | Barcelona |
| Period | 7/26/09 → 7/29/09 |
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All Science Journal Classification (ASJC) codes
- Computer Vision and Pattern Recognition
Cite this
Statistical classification of spatial relationships among mathematical symbols. / Aly, Walaa; Uchida, Seiichi; Fujiyoshi, Akio; Suzuki, Masakazu.
ICDAR2009 - 10th International Conference on Document Analysis and Recognition. 2009. p. 1350-1354 5277745 (Proceedings of the International Conference on Document Analysis and Recognition, ICDAR).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
}
TY - GEN
T1 - Statistical classification of spatial relationships among mathematical symbols
AU - Aly, Walaa
AU - Uchida, Seiichi
AU - Fujiyoshi, Akio
AU - Suzuki, Masakazu
PY - 2009/12/10
Y1 - 2009/12/10
N2 - In this paper, a statistical decision method for automatic classification of spatial relationships between each adjacent pair is proposed. Each pair is composed of mathematical symbols and/or alphabetical characters. Special treatment of mathematical symbols with variable size is important. This classification is important to recognize an accurate structure analysis module of math OCR. Experimental results on a very large database showed that the proposed method worked well with an accuracy of 99.57% by two important geometric feature relative size and relative position.
AB - In this paper, a statistical decision method for automatic classification of spatial relationships between each adjacent pair is proposed. Each pair is composed of mathematical symbols and/or alphabetical characters. Special treatment of mathematical symbols with variable size is important. This classification is important to recognize an accurate structure analysis module of math OCR. Experimental results on a very large database showed that the proposed method worked well with an accuracy of 99.57% by two important geometric feature relative size and relative position.
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UR - http://www.scopus.com/inward/citedby.url?scp=71249147245&partnerID=8YFLogxK
U2 - 10.1109/ICDAR.2009.90
DO - 10.1109/ICDAR.2009.90
M3 - Conference contribution
AN - SCOPUS:71249147245
SN - 9780769537252
T3 - Proceedings of the International Conference on Document Analysis and Recognition, ICDAR
SP - 1350
EP - 1354
BT - ICDAR2009 - 10th International Conference on Document Analysis and Recognition
ER -