Ricerc@Sapienza

The automatic distinction (domain separation) between handwriting (textual domain) and freehand drawing (graphical domain) elements into the same layer is a topic of great interest that still requires further investigation. This paper describes a machine learning based approach for the online separation of domain elements. The proposed approach presents two main innovative contributions. First, a new set of discriminative features is presented. Second, the use of a Support Vector Machine (SVM) classifier to properly separate the different elements.

Online separation between handwriting and freehand drawing is still an active research area
in the field of sketch-based interfaces. In the last years, most approaches in this area have
been focused on the use of statistical separation methods, which have achieved significant
results in terms of performance. More recently, Machine Learning (ML) techniques have
proven to be even more effective by treating the separation problem like a classification task.
Despite this, also in the use of these techniques several aspects can be still considered open