Precise Foreground Detection Algorithm Using Motion Estimation, Minima and Maxima Inside the Foreground Object

Muhammad Nawaz, John Cosmas, Pavlos I. Lazaridis, Zaharias D. Zaharis, Yue Zhang, Hamdullah Mohib

Research output: Contribution to journalArticle

2 Citations (Scopus)

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.
Original languageEnglish
Pages (from-to)725-731
Number of pages7
JournalIEEE Transactions on Broadcasting
Volume59
Issue number4
Early online date21 Oct 2013
DOIs
Publication statusPublished - Dec 2013
Externally publishedYes

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