Baseline extraction-driven Parsing of handwritten mathematical expressions

We generalize recursive baseline extraction algorithms for symbol layout analysis in math expressions so that handwritten strokes may be provided as input. Specifically, baseline extraction is used for lexical analysis in a modified LL(1) parser, returning a set of candidate symbols when the leftmost or next symbol along the current baseline (from left-to-right) is requested by the parser. Candidate symbols are used to produce a forest of parse trees, and the highest ranked parse returned. Hidden Markov Models (HMMs) are used for symbol classification, and horizontal adjacency between symbols is determined using two probabilistic quadratic classifiers, one for ascenders (e.g. `A´) and another for centered and descender symbols (e.g. `y´ and `x´). The system placed second in the CROHME 2011 handwritten math recognition competition.