Statistical classification of spatial relationships among mathematical symbols

Walaa Aly, Seiichi Uchida, Akio Fujiyoshi, Masakazu Suzuki

Research output: Chapter in Book/Report/Conference proceedingConference contribution

13 Citations (Scopus)

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 languageEnglish
Title of host publicationICDAR2009 - 10th International Conference on Document Analysis and Recognition
Pages1350-1354
Number of pages5
DOIs
Publication statusPublished - 2009
EventICDAR2009 - 10th International Conference on Document Analysis and Recognition - Barcelona, Spain
Duration: Jul 26 2009Jul 29 2009

Publication series

NameProceedings of the International Conference on Document Analysis and Recognition, ICDAR
ISSN (Print)1520-5363

Other

OtherICDAR2009 - 10th International Conference on Document Analysis and Recognition
CountrySpain
CityBarcelona
Period7/26/097/29/09

All Science Journal Classification (ASJC) codes

  • Computer Vision and Pattern Recognition

Fingerprint Dive into the research topics of 'Statistical classification of spatial relationships among mathematical symbols'. Together they form a unique fingerprint.

Cite this