One significant challenge in the recognition of off-line handwriting is in the interpretation of loop structures. Although this information is readily available in online representation, close proximity of strokes often merges their centers making them difficult to identify. In this paper a novel approach to the recovery of hidden loops in off-line scanned document images is presented. The proposed algorithm seeks blobs that resemble truncated ellipses. We use a sophisticated form analysis method based on mutual distance measurements between the two sides of a symmetric shape. The experimental results are compared with the ground truth of the online representations of each off-line word image. More than 86% percent of the meaningful loops are handled correctly.


    Zugriff

    Zugriff prüfen

    Verfügbarkeit in meiner Bibliothek prüfen

    Bestellung bei Subito €


    Exportieren, teilen und zitieren



    Titel :

    Hidden loop recovery for handwriting recognition


    Beteiligte:
    Doermann, D. (Autor:in) / Intrator, N. (Autor:in) / Rivin, E. (Autor:in) / Steinherz, T. (Autor:in)


    Erscheinungsdatum :

    01.01.2002


    Format / Umfang :

    450233 byte




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



    Hidden Loop Recovery for Handwriting Recognition

    Doermann, D. / Intrator, N. / Rivlin, E. et al. | British Library Conference Proceedings | 2002



    Hidden Markov Model Length Optimization for Handwriting Recognition Systems

    Zimmermann, M. / Bunke, H. | British Library Conference Proceedings | 2002


    Recognition of Off-Line Cursive Handwriting

    Abuhaiba, I. S. I. / Holt, M. J. J. / Datta, S. | British Library Online Contents | 1998


    Combining online and offline handwriting recognition

    Vinciarelli, A. / Perone, M. | IEEE | 2003