An incremental recognition method for online handwritten mathematical expressions

This paper presents an incremental recognition method for online handwritten mathematical expressions (MEs), which is used for busy recognition interface (recognition while writing) without large waiting time. We employ local processing strategy and focus on recent strokes. For the latest stroke, we perform segmentation, recognition and update of Cocke-Younger-Kasami (CYK) table. We also reuse the segmentation and recognition candidates in the previous processes. Moreover, using multi-thread reduces the waiting time. Experiments on our data set show the effectiveness of the incremental method not only in small waiting time but also keeping almost the same recognition rate of the batch recognition method without significant decrease. We also propose the combination of the two methods which succeeds the advantages of the both.