In this article, we have presented a morphology-based method for building recognition from FLIR image sequences captured by the midwave calibrated camera in dense urban areas. Based on the imaging parameters (the horizontal and vertical angle of field of view, the imaging distance, and the elevation), the imaging size of the building target can be determined in real time, and then the SE, which has a high correlation with the target's imaging size, has been generated. Additionally, to improve the performance of target detection and straight-line extraction, the line segment grouping method and the gradient-based straight-line extraction method are adopted. Experimental results show the algorithm can recognize the prominent building object with higher local contrast in FLIR image sequences in dense urban areas and maintain higher performance.


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    Titel :

    Morphology-based building target detection from forward-looking infrared imagery in dense urban areas


    Beteiligte:
    Li Zhang (Autor:in) / Tianxu Zhang (Autor:in) / Fan Peng (Autor:in) / Xiaoping Wang (Autor:in) / Yaxun Wei (Autor:in)

    Erschienen in:

    Erscheinungsdatum :

    01.12.2012


    Format / Umfang :

    2970076 byte




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




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