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    Precise foreground detection algorithm using motion estimation, minima and maxima inside the foreground object

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    Authors
    Nawaz, Muhammad
    Cosmas, John
    Lazaridis, Pavlos I.
    Zaharis, Zaharias D.
    Zhang, Yue
    Mohib, Hamdullah
    Affiliation
    Brunel University
    University of Bedfordshire
    Issue Date
    2013
    Subjects
    image sequences
    motion estimation
    object detection
    video signal processing
    
    Metadata
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    Abstract
    In this paper the precise foreground mask is obtained in a complex environment by applying simple and effective methods on a video sequence consisting of multi-colour and multiple foreground object environment. To detect moving objects we use a simple algorithm based on block-based motion estimation, which requires less computational time. To obtain a full and improved mask of the moving object, we use an opening-and-closing-by-reconstruction mechanism to identify the minima and maxima inside the foreground object by applying a set of morphological operations. This further enhances the outlines of foreground objects at various stages of image processing. Therefore, the algorithm does not require the knowledge of the background image. That is why it can be used in real world video sequences to detect the foreground in cases where we do not have a background model in advance. The comparative performance results demonstrate the effectiveness of the proposed algorithm.
    Citation
    Nawaz, M., Cosmas, J., Lazaridis, P.I., Zaharis, Z.D., Yue Zhang, Mohib, H. (2013) 'Precise Foreground Detection Algorithm Using Motion Estimation, Minima and Maxima Inside the Foreground Object', Broadcasting, IEEE Transactions on , 59 (4): 725-731
    Publisher
    IEEE
    Journal
    IEEE Transactions on Broadcasting
    URI
    http://hdl.handle.net/10547/335956
    DOI
    10.1109/TBC.2013.2282733
    Additional Links
    http://ieeexplore.ieee.org/lpdocs/epic03/wrapper.htm?arnumber=6642053
    Type
    Article
    Language
    en
    ISSN
    0018-9316
    1557-9611
    ae974a485f413a2113503eed53cd6c53
    10.1109/TBC.2013.2282733
    Scopus Count
    Collections
    Centre for Computer Graphics and Visualisation (CCGV)

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