Harit, Gaurav

Automated identification of mathematical expressions (MEs) is essential in transforming scientific and engineering documents into electronic form. Even though character and symbol recognizers have achieved commendable performance for digitizing documents, structure analysers still face a challenge in correctly interpreting the maths expressions. This review paper compares the salient aspects of past works dealing with structure analysis of printed and handwritten MEs. To the best of our knowledge, no previous work has done a systematic study of structural analysis methods in mathematical expression recognition. We present distinguishing aspects of different grammars and their production rules for semantic parsing of ME. Our study contributes by providing information on the existing datasets, their desirable properties, different evaluation measures, distinguishing aspects of techniques used and future research directions in structural analysis.

Structural analysis helps in parsing the mathematical expressions. Various approaches for structural analysis have been reported in literature, but they mainly deal with online and printed expressions. In this work, two-dimensional, stochastic context-free grammar is used for the structural analysis of offline handwritten mathematical expressions in a document image. The spatial relation between characters in an expression has been incorporated so that the structural variability in handwritten expressions can be tackled.