Wavelet Multi-Scale Transform Based Foreground Segmentation and Shadow Elimination

Ye-peng Guan
{"title":"Wavelet Multi-Scale Transform Based Foreground Segmentation and Shadow Elimination","authors":"Ye-peng Guan","doi":"10.2174/1876825300801010001","DOIUrl":null,"url":null,"abstract":"An algorithm using wavelet multi-scale transform for segmenting foreground moving objects and suppressing shadow is proposed. The optimal selection of threshold is automatically determined which does not require any complex supervised training, manual calibration or hypothesis. The proposed algorithm is efficient enough to segment foreground moving objects with low contrast against the background. The reference image is used to extract foreground no matter the objects enter the field of view before captured or not. The developed method is highly computationally cost-effective since it does not concern with complex computation model, color model or background statistics at a time. By compari- sons, it has been shown that the proposed approach is more robust and efficient to detect foreground and suppress shadow during coping with different indoors or outdoors circumstances.","PeriodicalId":147157,"journal":{"name":"The Open Signal Processing Journal","volume":"247 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2008-11-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"29","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"The Open Signal Processing Journal","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2174/1876825300801010001","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 29

Abstract

An algorithm using wavelet multi-scale transform for segmenting foreground moving objects and suppressing shadow is proposed. The optimal selection of threshold is automatically determined which does not require any complex supervised training, manual calibration or hypothesis. The proposed algorithm is efficient enough to segment foreground moving objects with low contrast against the background. The reference image is used to extract foreground no matter the objects enter the field of view before captured or not. The developed method is highly computationally cost-effective since it does not concern with complex computation model, color model or background statistics at a time. By compari- sons, it has been shown that the proposed approach is more robust and efficient to detect foreground and suppress shadow during coping with different indoors or outdoors circumstances.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
基于小波多尺度变换的前景分割与阴影消除
提出了一种基于小波多尺度变换的前景运动目标分割和阴影抑制算法。阈值的最佳选择是自动确定的,不需要任何复杂的监督训练,人工校准或假设。该算法能够有效分割背景对比度较低的前景运动目标。无论物体是否在捕获前进入视场,都使用参考图像提取前景。该方法不涉及复杂的计算模型、颜色模型或背景统计,具有较高的计算成本。对比结果表明,在不同的室内和室外环境下,该方法在前景检测和阴影抑制方面具有更强的鲁棒性和有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
A Fast Algorithm for the Demosaicing Problem Concerning the Bayer Pattern Side-Informed Image Watermarking Scheme Based on Dither Modulation in the Frequency Domain On the Enhancement of LDPC Codes Used in WiMAX Constrained Signals: A General Theory of Information Content and Detection Tailoring of Minimum Sidelobe Cosine-Sum Windows for High-Resolution Measurements
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1