A Machine Learning Approach for the Online Separation of Handwriting from Freehand Drawing

  • Danilo Avola
  • Marco Bernardi
  • Luigi CinqueEmail author
  • Gian Luca Foresti
  • Marco Raoul Marini
  • Cristiano Massaroni
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10484)


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.


Domain separation Handwriting Textual domain Freehand drawing Graphical domain SVM classifier 


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Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  • Danilo Avola
    • 1
  • Marco Bernardi
    • 2
  • Luigi Cinque
    • 2
    Email author
  • Gian Luca Foresti
    • 1
  • Marco Raoul Marini
    • 2
  • Cristiano Massaroni
    • 2
  1. 1.Department of Mathematics, Computer Science, and PhysicsUniversity of UdineUdineItaly
  2. 2.Department of Computer ScienceSapienza UniversityRomeItaly

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