A comparative study on methods and tools for handwritten mathematical expression recognition
Daniela S. Costa, C.A.B. Mello, Marcelo d’Amorim · 2021
Handwritten mathematical expression recognition (HMER) is a challenging task due to factors such as ambiguity, variety of writing styles, and complexity of two-dimensional writing. In this paper, we identify challenges in HMER applications through experiments that simulate real scenarios that go far beyond the usual cases found in literature: variations on luminance; different stroke width, inclination and color; different background pattern; and partially shaded images. The results of state-of-the-art methods (as TAP and Dense-WAP) and a commercial tool (MathPix) are analyzed, using the CROHME 2016 database. We proved that, although the area has had a lot of improvement in recent years, there are still issues to overcome.