So far the bottleneck of Chinese recognition, especially handwritten recognition, still lies in the effectiveness of feature-extraction to cater for various distortions and position shifting. In the paper, a novel method is proposed by applying a set of Gabor spatial filters with different directions and spatial frequencies to character images, in an effort to reach the optimum trade-off between feature stability and feature localization. While a classic self-organizing map is used for unsupervised clustering feature codes, a multi-staged LVQ with a fuzzy judgement unit is applied for the final recognition on the feature mapping result.<>


    Zugriff

    Zugriff prüfen

    Verfügbarkeit in meiner Bibliothek prüfen

    Bestellung bei Subito €


    Exportieren, teilen und zitieren



    Titel :

    Handwritten Chinese character recognition using spatial Gabor filters and self-organizing feature maps


    Beteiligte:
    Da Deng (Autor:in) / Chan, K.P. (Autor:in) / Yinglin Yu (Autor:in)


    Erscheinungsdatum :

    01.01.1994


    Format / Umfang :

    360439 byte




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



    Handwritten Chinese Character Recognition using Spatial Gabor Filters and Self-Organizing Feature Maps

    Deng, D. / Chan, K. P. / Yu, Y. et al. | British Library Conference Proceedings | 1994


    Recognition of gray character using gabor filters

    Peifeng Hu, / Yannan Zhao, / Zehong Yang, et al. | IEEE | 2002


    Recognition of Gray Character using Gabor Filters

    Hu, P. / Zhao, Y. / Wang, J. et al. | British Library Conference Proceedings | 2002


    Feature Extraction and Analysis of Handwritten Words in Gray-scale Images using Gabor Filters

    Buse, R. / Liu, Z.-Q. / IEEE; Signal Processing Society | British Library Conference Proceedings | 1994