Determining Points on Handwritten Mathematical Symbols
In a variety of applications, such as handwritten mathematics and diagram labelling, it is common to have symbols of many different sizes in use and for the writing not to follow simple baselines. In order to understand the scale and relative positioning of individual characters, it is necessary to identify the location of certain expected features. These are typically identified by particular points in the symbols, for example, the baseline of a lower case “p” would be identified by the lowest part of the bowl, ignoring the descender. We investigate how to find these special points automatically so they may be used in a number of problems, such as improving two-dimensional mathematical recognition and in handwriting neatening, while preserving the original style.
KeywordsHandwriting analysis Handwriting neatening Mathematical handwriting recognition Pen computing
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- 1.Smirnova, E., Watt, S.M.: A context for pen-based mathematical computing. In: Proceedings of the 2005 Maple Summer Workshop, Waterloo, Canada, pp. 409–422 (2005)Google Scholar
- 3.Pechwitz, M., Margner, V.: Baseline estimation for arabic handwritten words. In: Proceedings of Eighth International Workshop on Frontiers in Handwriting Recognition, pp. 479–484 (2002)Google Scholar
- 4.Infante Velázquez, M.T.: Metrics and neatening of handwritten characters. Master’s thesis, The University of Western Ontario, Canada (2010)Google Scholar
- 5.Watt, S.M., Underhill, T. (eds.): Ink Markup Language (InkML) W3C Recommendation (September 2011), http://www.w3.org/TR/InkML/
- 7.Zanibbi, R., Novins, K., Arvo, J., Zanibbi, K.: Aiding manipulation of handwritten mathematical expressions through style-preserving morphs. In: Proceedings of Graphics Interface 2001, pp. 127–134 (2001)Google Scholar
- 8.Hu, R., Watt, S.: Optimization of point selection on digital ink curves. In: Proceedings of 2012 International Conference on Frontiers in Handwriting Recognition (ICFHR), pp. 527–532 (September 2012)Google Scholar
- 9.Harouni, M., Mohamad, D., Rasouli, A.: Deductive method for recognition of on-line handwritten persian/arabic characters. In: Proceedings of 2010 The 2nd International Conference on Computer and Automation Engineering (ICCAE), vol. 5, pp. 791–795 (February 2010)Google Scholar
- 10.Watt, S.M.: Polynomial approximation in handwriting recognition. In: Proceedings of the 2011 International Workshop on Symbolic-Numeric Computation, SNC 2011, pp. 3–7. ACM (2011)Google Scholar
- 11.Golubitsky, O., Watt, S.M.: Online stroke modeling for handwriting recognition. In: Proceedings of the 2008 Conference of the Center for Advanced Studies on Collaborative Research: Meeting of Minds, CASCON 2008, pp. 6:72–6:80. ACM (2008)Google Scholar
- 12.Char, B.W., Watt, S.M.: Representing and characterizing handwritten mathematical symbols through succinct functional approximation. In: Proceedings of the Ninth International Conference on Document Analysis and Recognition, ICDAR 2007, vol. 02, pp. 1198–1202. IEEE Computer Society (2007)Google Scholar
- 14.Golubitsky, O., Mazalov, V., Watt, S.M.: Orientation-independent recognition of handwritten characters with integral invariants. In: Proceedings of Joint Conference of ASCM 2009 and MACIS 2009: Asian Symposium of Computer Mathematics and Mathematical Aspects of Computer and Information Sciences, ASCM 2009, pp. 252–261 (2009)Google Scholar
- 15.Golubitsky, O., Mazalov, V., Watt, S.M.: Toward affine recognition of handwritten mathematical characters. In: Proceedings of the 9th IAPR International Workshop on Document Analysis Systems, DAS 2010, pp. 35–42. ACM (2010)Google Scholar