Segmentation of Moving Object Using Background Subtraction Method in Complex Environments

Background subtraction is an extensively used approach to localize the moving object in a video sequence. However, detecting an object under the spatiotemporal behavior of background such as rippling of water, moving curtain and illumination change or low resolution is not a straightforward task. To...

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Main Authors: S. Kumar, J. S. Yadav
Format: Article
Language:English
Published: Spolecnost pro radioelektronicke inzenyrstvi 2016-06-01
Series:Radioengineering
Subjects:
Online Access:http://www.radioeng.cz/fulltexts/2016/16_02_0399_0408.pdf
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author S. Kumar
J. S. Yadav
author_facet S. Kumar
J. S. Yadav
author_sort S. Kumar
collection DOAJ
description Background subtraction is an extensively used approach to localize the moving object in a video sequence. However, detecting an object under the spatiotemporal behavior of background such as rippling of water, moving curtain and illumination change or low resolution is not a straightforward task. To deal with the above-mentioned problem, we address a background maintenance scheme based on the updating of background pixels by estimating the current spatial variance along the temporal line. The work is focused to immune the variation of local motion in the background. Finally, the most suitable label assignment to the motion field is estimated and optimized by using iterated conditional mode (ICM) under a Markovian framework. Performance evaluation and comparisons with the other well-known background subtraction methods show that the proposed method is unaffected by the problem of aperture distortion, ghost image, and high frequency noise.
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spelling doaj.art-8bf6a79381bc44afabde065143d07e372022-12-21T23:48:33ZengSpolecnost pro radioelektronicke inzenyrstviRadioengineering1210-25122016-06-01252399408Segmentation of Moving Object Using Background Subtraction Method in Complex EnvironmentsS. KumarJ. S. YadavBackground subtraction is an extensively used approach to localize the moving object in a video sequence. However, detecting an object under the spatiotemporal behavior of background such as rippling of water, moving curtain and illumination change or low resolution is not a straightforward task. To deal with the above-mentioned problem, we address a background maintenance scheme based on the updating of background pixels by estimating the current spatial variance along the temporal line. The work is focused to immune the variation of local motion in the background. Finally, the most suitable label assignment to the motion field is estimated and optimized by using iterated conditional mode (ICM) under a Markovian framework. Performance evaluation and comparisons with the other well-known background subtraction methods show that the proposed method is unaffected by the problem of aperture distortion, ghost image, and high frequency noise.http://www.radioeng.cz/fulltexts/2016/16_02_0399_0408.pdfBackground subtractionbackground modelinginitial motion fieldmorphology
spellingShingle S. Kumar
J. S. Yadav
Segmentation of Moving Object Using Background Subtraction Method in Complex Environments
Radioengineering
Background subtraction
background modeling
initial motion field
morphology
title Segmentation of Moving Object Using Background Subtraction Method in Complex Environments
title_full Segmentation of Moving Object Using Background Subtraction Method in Complex Environments
title_fullStr Segmentation of Moving Object Using Background Subtraction Method in Complex Environments
title_full_unstemmed Segmentation of Moving Object Using Background Subtraction Method in Complex Environments
title_short Segmentation of Moving Object Using Background Subtraction Method in Complex Environments
title_sort segmentation of moving object using background subtraction method in complex environments
topic Background subtraction
background modeling
initial motion field
morphology
url http://www.radioeng.cz/fulltexts/2016/16_02_0399_0408.pdf
work_keys_str_mv AT skumar segmentationofmovingobjectusingbackgroundsubtractionmethodincomplexenvironments
AT jsyadav segmentationofmovingobjectusingbackgroundsubtractionmethodincomplexenvironments