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Moving Object Detection Using Scanning Camera on a High-Precision Intelligent Holder

During the process of moving object detection in an intelligent visual surveillance system, a scenario with complex background is sure to appear. The traditional methods, such as “frame difference” and “optical flow”, may not able to deal with the problem very well. In such scenarios, we use a modif...

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Detalles Bibliográficos
Autores principales: Chen, Shuoyang, Xu, Tingfa, Li, Daqun, Zhang, Jizhou, Jiang, Shenwang
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5087542/
https://www.ncbi.nlm.nih.gov/pubmed/27775671
http://dx.doi.org/10.3390/s16101758
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author Chen, Shuoyang
Xu, Tingfa
Li, Daqun
Zhang, Jizhou
Jiang, Shenwang
author_facet Chen, Shuoyang
Xu, Tingfa
Li, Daqun
Zhang, Jizhou
Jiang, Shenwang
author_sort Chen, Shuoyang
collection PubMed
description During the process of moving object detection in an intelligent visual surveillance system, a scenario with complex background is sure to appear. The traditional methods, such as “frame difference” and “optical flow”, may not able to deal with the problem very well. In such scenarios, we use a modified algorithm to do the background modeling work. In this paper, we use edge detection to get an edge difference image just to enhance the ability of resistance illumination variation. Then we use a “multi-block temporal-analyzing LBP (Local Binary Pattern)” algorithm to do the segmentation. In the end, a connected component is used to locate the object. We also produce a hardware platform, the core of which consists of the DSP (Digital Signal Processor) and FPGA (Field Programmable Gate Array) platforms and the high-precision intelligent holder.
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spelling pubmed-50875422016-11-07 Moving Object Detection Using Scanning Camera on a High-Precision Intelligent Holder Chen, Shuoyang Xu, Tingfa Li, Daqun Zhang, Jizhou Jiang, Shenwang Sensors (Basel) Article During the process of moving object detection in an intelligent visual surveillance system, a scenario with complex background is sure to appear. The traditional methods, such as “frame difference” and “optical flow”, may not able to deal with the problem very well. In such scenarios, we use a modified algorithm to do the background modeling work. In this paper, we use edge detection to get an edge difference image just to enhance the ability of resistance illumination variation. Then we use a “multi-block temporal-analyzing LBP (Local Binary Pattern)” algorithm to do the segmentation. In the end, a connected component is used to locate the object. We also produce a hardware platform, the core of which consists of the DSP (Digital Signal Processor) and FPGA (Field Programmable Gate Array) platforms and the high-precision intelligent holder. MDPI 2016-10-21 /pmc/articles/PMC5087542/ /pubmed/27775671 http://dx.doi.org/10.3390/s16101758 Text en © 2016 by the authors; licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC-BY) license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Chen, Shuoyang
Xu, Tingfa
Li, Daqun
Zhang, Jizhou
Jiang, Shenwang
Moving Object Detection Using Scanning Camera on a High-Precision Intelligent Holder
title Moving Object Detection Using Scanning Camera on a High-Precision Intelligent Holder
title_full Moving Object Detection Using Scanning Camera on a High-Precision Intelligent Holder
title_fullStr Moving Object Detection Using Scanning Camera on a High-Precision Intelligent Holder
title_full_unstemmed Moving Object Detection Using Scanning Camera on a High-Precision Intelligent Holder
title_short Moving Object Detection Using Scanning Camera on a High-Precision Intelligent Holder
title_sort moving object detection using scanning camera on a high-precision intelligent holder
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5087542/
https://www.ncbi.nlm.nih.gov/pubmed/27775671
http://dx.doi.org/10.3390/s16101758
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