Speedup of Parsing for Recognition of Online Handwritten Mathematical Expressions
Anh Duc Le, Masaki Nakagawa · 2017
This paper proposes a method for speeding upparsing process for recognizing online handwritten mathematicalexpressions (OHME). We prune infeasible partitions in theparsing table to reduce the time for the parsing process. Lowscore partitions are candidates for pruning. Our method can beapplied for any parsing algorithms that use score functions. Inthis paper, we use a stroke order free system as a baseline system.The method is as follows. First, we analyze the scores ofpartitions in each row of the parsing table. Then, we determine athreshold for each row to prune low score partitions. Finally, weemploy these thresholds to prune low score partitions on thebaseline recognition system. The results of evaluations of ourmethod on the CROHME 2014 database show that therecognition process is speeded up by 3.46 times and 4.97 timeswhile recognition rate is reduced only 0.31 point and 0.71 point,respectively.