Progressive structural analysis for dynamic recognition of on-line handwritten mathematical expressions

Structural analysis in handwritten mathematical expressions focuses on interpreting the recognized symbols using geometrical information such as relative sizes and positions of the symbols. Most existing approaches rely on hand-crafted grammar rules to identify semantic relationships among the recognized mathematical symbols. They could easily fail when writing errors occurred. Moreover, they assume the availability of the whole mathematical expression before being able to analyze the semantic information of the expression. To tackle these problems, we propose a progressive structural analysis (PSA) approach for dynamic recognition of handwritten mathematical expressions. The proposed PSA approach is able to provide analysis result immediately after each written input symbol. This has an advantage that users are able to detect any recognition errors immediately and correct only the mis-recognized symbols rather than the whole expression. Experiments conducted on 57 most commonly used mathematical expressions have shown that the PSA approach is able to achieve very good performance results.

[1]  Jesse James Garrett Ajax: A New Approach to Web Applications , 2007 .

[2]  Raúl Rojas,et al.  Recognition of On-line Handwritten Mathematical Expressions Using a Minimum Spanning Tree Construction and Symbol Dominance , 2003, GREC.

[3]  Dit-Yan Yeung,et al.  An efficient syntactic approach to structural analysis of on-line handwritten mathematical expressions , 2000, Pattern Recognit..

[4]  William Pearlman,et al.  Visual Communications and Image Processing IV , 1989 .

[5]  Leslie Lamport,et al.  LATEX. A document preparation system. User's Guide and Reference Manual , 1996 .

[6]  Volker Sorge,et al.  Towards a Parser for Mathematical Formula Recognition , 2006, MKM.

[7]  Dorothea Blostein,et al.  Mathematics recognition using graph rewriting , 1995, Proceedings of 3rd International Conference on Document Analysis and Recognition.

[8]  Stephane Lavirotte Optical formula recognition , 1997, Proceedings of the Fourth International Conference on Document Analysis and Recognition.

[9]  Richard Zanibbi,et al.  Recognizing Mathematical Expressions Using Tree Transformation , 2002, IEEE Trans. Pattern Anal. Mach. Intell..

[10]  Masakazu Suzuki,et al.  Structural Analysis of Mathematical Formulae with Verification Based on Formula Description Grammar , 2006, Document Analysis Systems.

[11]  Dit-Yan Yeung,et al.  Mathematical expression recognition: a survey , 2000, International Journal on Document Analysis and Recognition.

[12]  Richard J. Fateman,et al.  Optical Character Recognition and Parsing of Typeset Mathematics1 , 1996, J. Vis. Commun. Image Represent..

[13]  C. Peng SCALABLE VECTOR GRAPHICS (SVG) , 2000 .

[14]  Raúl Rojas,et al.  Recognition of on-line handwritten mathematical expressions in the E-Chalk system - an extension , 2005, Eighth International Conference on Document Analysis and Recognition (ICDAR'05).

[15]  P. A. Chou,et al.  Recognition of Equations Using a Two-Dimensional Stochastic Context-Free Grammar , 1989, Other Conferences.

[16]  Dit-Yan Yeung,et al.  Elastic structural matching for online handwritten alphanumeric character recognition , 1998, Proceedings. Fourteenth International Conference on Pattern Recognition (Cat. No.98EX170).

[17]  Andreas Neumann Scalable Vector Graphics (SVG) , 2008, Encyclopedia of GIS.

[18]  Dave Crane,et al.  Ajax in Action , 2005 .

[19]  A. Kosmala,et al.  ON-LINE HANDWRITTEN FORMULA RECOGNITION , 1999 .

[20]  Gerhard Rigoll,et al.  On-line handwritten formula recognition using statistical methods , 1998, Proceedings. Fourteenth International Conference on Pattern Recognition (Cat. No.98EX170).