A new color image segmentation algorithm based on semi-supervised clustering is proposed, which integrates limited human assistance, a user indicates the relationship of some different regions in an image by mouse, to get the final accurate segmentation result which satisfies the prior segmentation constraints. The algorithm first has the image quantified and then clusters in the quantified color space with prior segmentation information. Experiment results show that the proposed algorithm is effective and has high value of utility.


    Zugriff

    Zugriff prüfen

    Verfügbarkeit in meiner Bibliothek prüfen

    Bestellung bei Subito €


    Exportieren, teilen und zitieren



    Titel :

    A semi-supervised color image segmentation method


    Beteiligte:
    Yuntao Qian, (Autor:in) / Wenwu Si, (Autor:in)


    Erscheinungsdatum :

    01.01.2005


    Format / Umfang :

    389403 byte




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



    A Semi-supervised Color Image Segmentation Method

    Qian, Y. / Si, W. | British Library Conference Proceedings | 2005


    Color Image Segmentation Using Graph-Based Semi-Supervised Learning

    Chen, R. / Sun, J. / Xu, Z. | British Library Online Contents | 2011


    Random walks in directed hypergraphs and application to semi-supervised image segmentation

    Ducournau, A. l. / Bretto, A. | British Library Online Contents | 2014


    Scale selection for supervised image segmentation

    Li, Y. / Tax, D. M. / Loog, M. | British Library Online Contents | 2012


    Color-Based Free-Space Segmentation Using Online Disparity-Supervised Learning

    Sanberg, Willem P. / Dubbelman, Gijs / With, Peter H. N. de | IEEE | 2015