Motion Objects Segmentation and Shadow Suppressing without Background Learning

An approach to segmenting motion objects and suppressing shadows without background learning has been developed. Since wavelet transformation indicates the position of sharper variation, it is adopted to extract the information contents with the most meaningful features based on two successive video...

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Main Author: Y.-P. Guan
Format: Article
Language:English
Published: Wiley 2014-01-01
Series:Journal of Engineering
Online Access:http://dx.doi.org/10.1155/2014/615198
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author Y.-P. Guan
author_facet Y.-P. Guan
author_sort Y.-P. Guan
collection DOAJ
description An approach to segmenting motion objects and suppressing shadows without background learning has been developed. Since wavelet transformation indicates the position of sharper variation, it is adopted to extract the information contents with the most meaningful features based on two successive video frames only. According to the fact that the saturation component is lower in the region of shadow and is independent of the brightness, HSV color space is selected to extract foreground motion region and suppress shadow instead of other color models. A local adaptive thresholding approach is proposed to extract initial binary motion masks based on the results of the wavelet transformation. A foreground reclassification is developed to get an optimal segmentation by fusion of mode filtering, connectivity analysis, and spatial-temporal correlation. Comparative studies with some investigated methods have indicated the superior performance of the proposal in extracting motion objects and suppressing shadows from cluttered contents with dynamic scene variation and crowded environments.
format Article
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institution Kabale University
issn 2314-4904
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language English
publishDate 2014-01-01
publisher Wiley
record_format Article
series Journal of Engineering
spelling doaj-art-9a68deb35a3543629cc0977a6c81c8dc2025-02-03T05:50:23ZengWileyJournal of Engineering2314-49042314-49122014-01-01201410.1155/2014/615198615198Motion Objects Segmentation and Shadow Suppressing without Background LearningY.-P. Guan0School of Communication and Information Engineering, Shanghai University, 99 Shangda Road, Shanghai 200444, ChinaAn approach to segmenting motion objects and suppressing shadows without background learning has been developed. Since wavelet transformation indicates the position of sharper variation, it is adopted to extract the information contents with the most meaningful features based on two successive video frames only. According to the fact that the saturation component is lower in the region of shadow and is independent of the brightness, HSV color space is selected to extract foreground motion region and suppress shadow instead of other color models. A local adaptive thresholding approach is proposed to extract initial binary motion masks based on the results of the wavelet transformation. A foreground reclassification is developed to get an optimal segmentation by fusion of mode filtering, connectivity analysis, and spatial-temporal correlation. Comparative studies with some investigated methods have indicated the superior performance of the proposal in extracting motion objects and suppressing shadows from cluttered contents with dynamic scene variation and crowded environments.http://dx.doi.org/10.1155/2014/615198
spellingShingle Y.-P. Guan
Motion Objects Segmentation and Shadow Suppressing without Background Learning
Journal of Engineering
title Motion Objects Segmentation and Shadow Suppressing without Background Learning
title_full Motion Objects Segmentation and Shadow Suppressing without Background Learning
title_fullStr Motion Objects Segmentation and Shadow Suppressing without Background Learning
title_full_unstemmed Motion Objects Segmentation and Shadow Suppressing without Background Learning
title_short Motion Objects Segmentation and Shadow Suppressing without Background Learning
title_sort motion objects segmentation and shadow suppressing without background learning
url http://dx.doi.org/10.1155/2014/615198
work_keys_str_mv AT ypguan motionobjectssegmentationandshadowsuppressingwithoutbackgroundlearning