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        <identifier>oai:meral.edu.mm:recid/3047</identifier>
        <datestamp>2021-12-13T07:58:34Z</datestamp>
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          <dc:title>Background Subtraction and Foreground Detection based on Codebook Model with Kalman Filter</dc:title>
          <dc:creator>Su Su Aung</dc:creator>
          <dc:creator>Zin Mar Kyu</dc:creator>
          <dc:description>Foreground object extraction is an important
subject for computer vision applications. The
separation of foreground objects form the
background is the crucial step in application
such as video surveillance. In order to extract
foreground object from a video scene, a
background model which can represent dynamic
changes in the scene is required. A robust,
accurate and high performance approach is still
a great challenge today. In this paper, the
background modeling approach based on
Codebook model with Kalman Filter is
presented. This approach can be used to extract
foreground objects from the video stream. The
Lab color space is used in this approach to
calculate color difference between two pixels
using CIEDE2000 color difference formula.
Extracted foreground object from video sequence
using this approach is useful for object detection
in video surveillance applications.</dc:description>
          <dc:date>2017-02-17</dc:date>
          <dc:identifier>http://hdl.handle.net/20.500.12678/0000003047</dc:identifier>
          <dc:identifier>https://meral.edu.mm/records/3047</dc:identifier>
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