BREADER: A MODULAR FRAMEWORK FOR VISION RECOGNITION OF MATHEMATICAL-LOGICAL STRUCTURES

Celia Salmim Rafael, Jorge Simao

Abstract

We describe a system that uses image processing and computer vision techniques to discover and recognize mathematical, logical, geometric, and other structures and symbols from bit-map images. The system uses a modular architecture to allow easy incorporation of new kinds of object recognizers. The systems uses a ``blackboard'' data-structure to retain the list of objects that have been recognized. Particular object recognizers check this list to discover new objects. Initially, objects are simple pixel clusters resulting from image-processing and segmentation operations. First-level object recognizers include symbol/character recognizers and basic geometric elements. Higher-level object recognizers collect lower-level objects and build more complex objects. This includes mathematical-logical expressions, and complex geometric elements such as polylines, graphs, and others. The recognized objects and structures can be exported to a variety of vector graphic languages and type-setting systems, such as SVG and LaTeX.

References

  1. Blostein, D. and Grbavec, A. (1996). Recognition of mathematical notation.
  2. C.C. Tappert, C. S. and Wakahara, T. (1990). The state of the art in on-line handwriting recognition. IEEE Transactions on Pattern Analysis and Machine Intelligence, 12:787-808.
  3. Chan, K.-F. and Yeung, D.-Y. (2000). Mathematical expression recognition: a survey. IJDAR, 3(1):3-15.
  4. Chung, R., Mirica, P., and Plimmer, B. (2005). Inkkit: a generic design tool for the tablet pc. In CHINZ 7805: Proceedings of the 6th ACM SIGCHI New Zealand chapter's international conference on Computerhuman interaction, pages 29-30. ACM.
  5. Freeman, I. J. and Plimmer, B. (2007). Connector semantics for sketched diagram recognition. In AUIC 7807: Proceedings of the eight Australasian conference on User interface, pages 71-78. Australian Computer Society, Inc.
  6. Ha, J., Haralick, R., and Phillips, I. (1995). Understanding mathematical expressions from document images. icdar, 02:956.
  7. Kara, L. B. and Stahovich, T. F. (2004). Hierarchical parsing and recognition of hand-sketched diagrams. In UIST 7804: Proceedings of the 17th annual ACM symposium on User interface software and technology, pages 13-22, New York, NY, USA. ACM.
  8. Lee, W., Kara, L. B., and Stahovich, T. F. (2007). An efficient graph-based recognizer for hand-drawn symbols. Comput. Graph., 31(4):554-567.
  9. Li, M.-H. H. X.-D. T. N. (2006). Structural analysis of printed mathematical expressions based on combined strategy. Machine Learning and Cybernetics, 2006 International Conference, pages 3354 - 3358.
  10. Miller, E. G. and Viola, P. A. (1998). Ambiguity and constraint in mathematical expression recognition. Nat. Conf. on Artif. Intell., pages 784-792.
  11. Mori, S., Suen, C., , and Yamamoto, K. (1992). Historical review of ocr research and development. Proceedings of the IEEE, 80:1029-1058.
  12. Nii, P. (1986). Blackboard systems part two: Blackboard application systems. AI Mag., 7(3):82-106.
  13. Rjean Plamond, S. N. S. (2000). On-line and off-line handwriting recognition: A comprehensive survey. IEEE Transactions on Pattern Analysis and Machine Intelligence, 22(1):63-84.
  14. Smith, J. (1998). The Book. The publishing company, London, 2nd edition.
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Paper Citation


in Bibtex Style

@conference{visapp09,
author={Celia Salmim Rafael and Jorge Simao},
title={BREADER: A MODULAR FRAMEWORK FOR VISION RECOGNITION OF MATHEMATICAL-LOGICAL STRUCTURES},
booktitle={Proceedings of the Fourth International Conference on Computer Vision Theory and Applications - Volume 2: VISAPP, (VISIGRAPP 2009)},
year={2009},
pages={249-255},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0001808702490255},
isbn={978-989-8111-69-2},
}


in Harvard Style

Salmim Rafael C. and Simao J. (2009). BREADER: A MODULAR FRAMEWORK FOR VISION RECOGNITION OF MATHEMATICAL-LOGICAL STRUCTURES . In Proceedings of the Fourth International Conference on Computer Vision Theory and Applications - Volume 2: VISAPP, (VISIGRAPP 2009) ISBN 978-989-8111-69-2, pages 249-255. DOI: 10.5220/0001808702490255


in EndNote Style

TY - CONF
JO - Proceedings of the Fourth International Conference on Computer Vision Theory and Applications - Volume 2: VISAPP, (VISIGRAPP 2009)
TI - BREADER: A MODULAR FRAMEWORK FOR VISION RECOGNITION OF MATHEMATICAL-LOGICAL STRUCTURES
SN - 978-989-8111-69-2
AU - Salmim Rafael C.
AU - Simao J.
PY - 2009
SP - 249
EP - 255
DO - 10.5220/0001808702490255