Security & Inspection X-Ray Systems is widely used by custom to accomplish some security missions by inspecting import-export cargo. Due to the specificity of cargo X-Ray image, such as overlap, viewpoint dependence, and variants of cargo categories, it couldn't be understood easily like natural ones by human. Even for experienced screeners, it's very difficult to judge cargo category and contraband. In this paper, cargo X-Ray image is described by joint shape and texture feature, which could reflect both cargo stacking mode and interior details. Classification performance is compared with the benchmark method by top hit 1, 3, 5 ratio, and it's demonstrated that good performance is achieved here. In addition, we also discuss X-Ray image property and explore some reasons why cargo classification under X-Ray is very difficult.


    Zugriff

    Zugriff prüfen

    Verfügbarkeit in meiner Bibliothek prüfen

    Bestellung bei Subito €


    Exportieren, teilen und zitieren



    Titel :

    Joint Shape and Texture Based X-Ray Cargo Image Classification


    Beteiligte:
    Zhang, Jian (Autor:in) / Zhang, Li (Autor:in) / Zhao, Ziran (Autor:in) / Liu, Yaohong (Autor:in) / Gu, Jianping (Autor:in) / Li, Qiang (Autor:in) / Zhang, Duokun (Autor:in)


    Erscheinungsdatum :

    2014-06-01


    Format / Umfang :

    1273765 byte





    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



    Texture classification for content-based image retrieval

    Pirrone, R. / La Cascia, M. | IEEE | 2001


    Texture Classification for Content-Based Image Retrieval

    Pirrone, R. / La Cascia, M. / IEEE | British Library Conference Proceedings | 2001


    Unsupervised classification of image texture

    Sidorova, V. S. | British Library Online Contents | 2008



    Optimal Bit Allocation for Joint Contour-Based Shape Coding and Shape Adaptive Texture Coding

    Bandyopadhyay, S. K. / Kondi, L. P. | British Library Conference Proceedings | 2005