A System for Recognizing Online Handwritten Mathematical Expressions and Improvement of Structure Analysis

This paper presents a system for recognizing online handwritten mathematical expressions (MEs) and improvement of structure analysis. We represent MEs in Context Free Grammars (CFGs) and employ the Cocke-Younger-Kasami (CYK) algorithm to parse 2D structure of on-line handwritten MEs and select the best interpretation in terms of symbol segmentation, recognition and structure analysis. We propose a method to learn structural relations from training patterns without any heuristic decisions by using two SVM models. We employ stroke order to reduce the complexity of the parsing algorithm. Moreover, we revise structure analysis. Even though CFG does not resolve ambiguities in some cases, our method still gives users a list of candidates that contain expecting result. We evaluate our method in the CROHME 2013 database and demonstrate the improvement of our system in recognition rate as well as processing time.