This paper proposes a model for recovering writing sequence from offline handwritten Chinese character image. In this model, a 4-layer hierarchy is presented to model Chinese character, where characters, components, subcomponents and strokes are located at each layer, respectively. Characters are decomposed to components and components are decomposed to subcomponents in turn by four decomposing operators. The totally-ordered relations among subcomponents are retrieved by defining the corresponding rules between decomposed relations and a partially-ordered set (poset) of subcomponents, and the writing orders of subcomponent are recovered by classifying strokes and crossing stroke pairs. Finally, experimental results show that our method is effective and accurate.


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    A Model for Recovering Writing Sequence from Offline Handwritten Chinese Character Image


    Contributors:


    Publication date :

    2008-05-01


    Size :

    514624 byte




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English





    Discriminative Training for HMM-Based Offline Handwritten Character Recognition

    Nopsuwanchai, R. / Povey, D. / Institute of Electrical and Electronics Engineers | British Library Conference Proceedings | 2003


    Handwritten Chinese Character Recognition: Alternatives to Nonlinear Normalization

    Liu, C. / Sako, H. / Fujisawa, H. et al. | British Library Conference Proceedings | 2003