LATEX (2nd ed.): a document preparation system: user's guide and reference manual
LATEX (2nd ed.): a document preparation system: user's guide and reference manual
Recognizing Mathematical Expressions Using Tree Transformation
IEEE Transactions on Pattern Analysis and Machine Intelligence
ICDAR '97 Proceedings of the 4th International Conference on Document Analysis and Recognition
Mathematics recognition using graph rewriting
ICDAR '95 Proceedings of the Third International Conference on Document Analysis and Recognition (Volume 1) - Volume 1
On-Line Handwritten Formula Recognition Using Statistical Methods
ICPR '98 Proceedings of the 14th International Conference on Pattern Recognition-Volume 2 - Volume 2
Elastic Structural Matching for On-Line Handwritten Alphanumeric Character Recognition
ICPR '98 Proceedings of the 14th International Conference on Pattern Recognition-Volume 2 - Volume 2
Ajax in Action
Recognition of On-Line Handwritten Mathematical Expressions in the E-Chalk System - An Extension
ICDAR '05 Proceedings of the Eighth International Conference on Document Analysis and Recognition
Towards a parser for mathematical formula recognition
MKM'06 Proceedings of the 5th international conference on Mathematical Knowledge Management
Structural analysis of mathematical formulae with verification based on formula description grammar
DAS'06 Proceedings of the 7th international conference on Document Analysis Systems
Towards a web-based progressive handwriting recognition environment for mathematical problem solving
Expert Systems with Applications: An International Journal
CEC'09 Proceedings of the Eleventh conference on Congress on Evolutionary Computation
A rule-based approach to form mathematical symbols in printed mathematical expressions
MIWAI'11 Proceedings of the 5th international conference on Multi-Disciplinary Trends in Artificial Intelligence
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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.