Thresholding is the basic way for traffic image processing. Two-dimensional (2-D) thresholding methods can get better results. They used a threshold vector to divide a 2-D histogram into object, background, edge/noise three parts. Object and background parts were the common parts of grayscale information and spatial information. Mutual information focuses on studying the cross-section between entropies of two distributions, so it was considered to improve some disadvantages of the current 2-D thresholding methods. Experimental results showed that the proposed method could get better results.


    Zugriff

    Zugriff prüfen

    Verfügbarkeit in meiner Bibliothek prüfen

    Bestellung bei Subito €


    Exportieren, teilen und zitieren



    Titel :

    Traffic image segmentation based on maximum posteriori mutual information


    Beteiligte:
    Cao, Li (Autor:in) / Shi, Zhong-ke (Autor:in) / Chen, Wen (Autor:in)


    Erscheinungsdatum :

    2009-06-01


    Format / Umfang :

    1495723 byte





    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



    Traffic Image Segmentation Based on Maximum Posteriori Mutual Information

    Cao, L. / Shi, Z.-k. / Chen, W. | British Library Conference Proceedings | 2009



    Maximum a posteriori image registration/motion estimation

    Oshman, Yaakov / Menis, Baruch | AIAA | 1994


    Local Mutual Information for Dissimilarity-Based Image Segmentation

    Gueguen, L. | British Library Online Contents | 2014


    Maximum a Posteriori Image Restoration Based on a New Directional Continuous Edge Image Prior

    Chantas, G. / Galatsanos, N. / Likas, A. | British Library Conference Proceedings | 2005