Detection and clearance of a buried are difficult problems with lots of environmental and economical implication. In this work, the mine detection is tackled in a broader context of preprocessing and texture segmentation for the data associated with infrared sensor. Principal component analysis is used to enhance the contrast by extracting the whole dynamic information contained in a sequence of images. Texture parameters, and fuzzy C-means clustering method are proposed to segment background and mine like objects. For the residual clutter in a segmented image, a post-processing step is employed based on morphological reconstruction filter that yields accurate detection result.


    Zugriff

    Zugriff über TIB

    Verfügbarkeit in meiner Bibliothek prüfen

    Bestellung bei Subito €


    Exportieren, teilen und zitieren



    Titel :

    Fuzzy C-means and mathematical morphology for mine detection in IR image


    Beteiligte:
    Sawsan, M. (Autor:in) / Ayman, E.D. (Autor:in) / Ahmed, B. (Autor:in) / Hanan, A.K. (Autor:in)


    Erscheinungsdatum :

    2003


    Format / Umfang :

    4 Seiten, 16 Quellen




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Print


    Sprache :

    Englisch




    Fuzzy Mathematical Morphology approach in Image Processing

    Yee Yee Htun / Dr. Khaing Khaing Aye | BASE | 2008

    Freier Zugriff

    Multiscale Image Filtering and Segmentation by Means of Adaptive Neighborhood Mathematical Morphology

    Debayle, J. / Pinoli, J.-C. | British Library Conference Proceedings | 2005



    Fuzzy clustering for land mine detection

    Frigui, H. / Gader, P. / Keller, J. | Tema Archiv | 1998


    Interval-Valued and Intuitionistic Fuzzy Mathematical Morphologies as Special Cases of Formula Not Shown -Fuzzy Mathematical Morphology

    Sussner, P. / Nachtegael, M. / Mélange, T. et al. | British Library Online Contents | 2012