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dc.contributor.authorNawaz, Muhammaden
dc.contributor.authorCosmas, Johnen
dc.contributor.authorLazaridis, Pavlos I.en
dc.contributor.authorZaharis, Zaharias D.en
dc.contributor.authorZhang, Yueen
dc.contributor.authorMohib, Hamdullahen
dc.date.accessioned2014-11-21T13:56:44Z
dc.date.available2014-11-21T13:56:44Z
dc.date.issued2013
dc.identifier.citationNawaz, 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): 725-731en
dc.identifier.issn0018-9316
dc.identifier.issn1557-9611
dc.identifier.doi10.1109/TBC.2013.2282733
dc.identifier.urihttp://hdl.handle.net/10547/335956
dc.description.abstractIn 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.
dc.language.isoenen
dc.publisherIEEEen
dc.relation.urlhttp://ieeexplore.ieee.org/lpdocs/epic03/wrapper.htm?arnumber=6642053en
dc.subjectimage sequencesen
dc.subjectmotion estimationen
dc.subjectobject detectionen
dc.subjectvideo signal processingen
dc.titlePrecise foreground detection algorithm using motion estimation, minima and maxima inside the foreground objecten
dc.typeArticleen
dc.contributor.departmentBrunel Universityen
dc.contributor.departmentUniversity of Bedfordshireen
dc.identifier.journalIEEE Transactions on Broadcastingen
html.description.abstractIn 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.


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