An Online Fuzzy Approach to the Structural Analysis of Handwritten Mathematical Expressions

Genoe, Ray; Fitzgerald, J.A.; Kechadi, Tahar

doi:10.1109/fuzzy.2006.1681721

Cited by 10 publications

(1 citation statement)

References 6 publications

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“…These methods are discussed further in Section 4.6. Some more recent parsing methods that model uncertainty include fuzzy-logic based parsing [44,53], and A*-penalty-based search [122].…”

Section: Mathematical Content Interpretationmentioning

confidence: 99%

Recognition and retrieval of mathematical expressions

Zanibbi

Blostein

2011

IJDAR

230

112

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Document recognition and retrieval technologies complement one another, providing improved access to increasingly large document collections. While recognition and retrieval of textual information is fairly mature, with wide-spread availability of Optical Character Recognition (OCR) and text-based search engines, recognition and retrieval of graphics such as images, figures, tables, diagrams, and mathematical expressions are in comparatively early stages of research. This paper surveys the state of the art in recognition and retrieval of mathematical expressions, organized around four key problems in math retrieval (query construction, normalization, indexing, and relevance feedback), and four key problems in math recognition (detecting expressions, detecting and classifying symbols, analyzing symbol layout, and constructing a representation of meaning). Of special interest is the machine learning problem of jointly optimizing the component algorithms in a math recognition system, and developing effective indexing, retrieval and relevance feedback algorithms for math retrieval. Another important open problem is developing user interfaces that seamlessly integrate recognition and retrieval. Activity in these important research areas is increasing, in part because math notation provides an excellent domain for studying problems common to many document and graphics recognition and retrieval applications, and also because mature applications will likely provide substantial benefits for education, research, and mathematical literacy.

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“…These methods are discussed further in Section 4.6. Some more recent parsing methods that model uncertainty include fuzzy-logic based parsing [44,53], and A*-penalty-based search [122].…”

Section: Mathematical Content Interpretationmentioning

confidence: 99%