A machine learning approach for the online separation of handwriting from freehand drawing

Abstract

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. Experimental results on a wide range of application domains show the robustness of the proposed method and prove the validity of the proposed approach.