Smoke detection for static cameras

This paper describes the smoke detection for static cameras. The background subtraction was used to determine moving objects. Color characteristics were utilized to distinguish smoke regions and other scene members. Separate pixels were united into blobs by morphology operations and connected compon...

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Autore principale: Cáceres Hernández, Danilo (author)
Altri autori: Hyun Jo, Kang (author), Filonenko, Alexander (author)
Natura: article
Lingua:inglese
Pubblicazione: 2018
Soggetti:
Accesso online:https://ieeexplore.ieee.org/abstract/document/7103719/
http://ridda2.utp.ac.pa/handle/123456789/5084
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author Cáceres Hernández, Danilo
author2 Hyun Jo, Kang
Filonenko, Alexander
author2_role author
author
author_browse Cáceres Hernández, Danilo
Filonenko, Alexander
Hyun Jo, Kang
author_facet Cáceres Hernández, Danilo
Hyun Jo, Kang
Filonenko, Alexander
author_role author
collection Repositorio Institucional de documento digitales de acceso abierto de la UTP
dc.creator.none.fl_str_mv Cáceres Hernández, Danilo
Hyun Jo, Kang
Filonenko, Alexander
dc.date.none.fl_str_mv 01/28/2015
01/28/2015
2018-06-28T20:38:51Z
2018-06-28T20:38:51Z
2018-06-28T20:38:51Z
2018-06-28T20:38:51Z
dc.format.none.fl_str_mv application/pdf
text/html
dc.identifier.none.fl_str_mv https://ieeexplore.ieee.org/abstract/document/7103719/
http://ridda2.utp.ac.pa/handle/123456789/5084
http://ridda2.utp.ac.pa/handle/123456789/5084
dc.language.none.fl_str_mv eng
dc.rights.none.fl_str_mv info:eu-repo/semantics/embargoedAccess
dc.source.none.fl_str_mv reponame:Repositorio Institucional de documento digitales de acceso abierto de la UTP
instname:Universidad Tecnológica de Panamá
instacron:U Tecnológica de Panamá
dc.subject.none.fl_str_mv Image color analysis
Cameras,
Image edge detection
Videos
Image resolution
Morphology
Probability
Image color analysis
Cameras,
Image edge detection
Videos
Image resolution
Morphology
Probability
dc.title.none.fl_str_mv Smoke detection for static cameras
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
description This paper describes the smoke detection for static cameras. The background subtraction was used to determine moving objects. Color characteristics were utilized to distinguish smoke regions and other scene members. Separate pixels were united into blobs by morphology operations and connected components labeling methods. The image is then refined by boundary roughness and edge density to decrease amount of false detections. Results of the current frame are compared to the previous one in order to check the behavior of objects in time domain.
eu_rights_str_mv embargoedAccess
format article
id lrtest_de4355437fed5f88b5c1e5e5d415f66a
instacron_str U Tecnológica de Panamá
institution U Tecnológica de Panamá
instname_str Universidad Tecnológica de Panamá
language eng
network_acronym_str lrtest
network_name_str lr
oai_identifier_str oai:ridda2.utp.ac.pa:123456789/5084
publishDate 2018
publishDateSort 2018
reponame_str Repositorio Institucional de documento digitales de acceso abierto de la UTP
repository.mail.fl_str_mv
repository.name.fl_str_mv
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spelling Smoke detection for static camerasCáceres Hernández, DaniloHyun Jo, KangFilonenko, AlexanderImage color analysisCameras,Image edge detectionVideosImage resolutionMorphologyProbabilityImage color analysisCameras,Image edge detectionVideosImage resolutionMorphologyProbabilityThis paper describes the smoke detection for static cameras. The background subtraction was used to determine moving objects. Color characteristics were utilized to distinguish smoke regions and other scene members. Separate pixels were united into blobs by morphology operations and connected components labeling methods. The image is then refined by boundary roughness and edge density to decrease amount of false detections. Results of the current frame are compared to the previous one in order to check the behavior of objects in time domain.This paper describes the smoke detection for static cameras. The background subtraction was used to determine moving objects. Color characteristics were utilized to distinguish smoke regions and other scene members. Separate pixels were united into blobs by morphology operations and connected components labeling methods. The image is then refined by boundary roughness and edge density to decrease amount of false detections. Results of the current frame are compared to the previous one in order to check the behavior of objects in time domain.2018-06-28T20:38:51Z2018-06-28T20:38:51Z2018-06-28T20:38:51Z2018-06-28T20:38:51Z01/28/201501/28/2015info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdftext/htmlhttps://ieeexplore.ieee.org/abstract/document/7103719/http://ridda2.utp.ac.pa/handle/123456789/5084http://ridda2.utp.ac.pa/handle/123456789/5084enginfo:eu-repo/semantics/embargoedAccessreponame:Repositorio Institucional de documento digitales de acceso abierto de la UTPinstname:Universidad Tecnológica de Panamáinstacron:U Tecnológica de Panamáoai:ridda2.utp.ac.pa:123456789/50842021-07-06T15:34:54Z
spellingShingle Smoke detection for static cameras
Cáceres Hernández, Danilo
Image color analysis
Cameras,
Image edge detection
Videos
Image resolution
Morphology
Probability
Image color analysis
Cameras,
Image edge detection
Videos
Image resolution
Morphology
Probability
status_str publishedVersion
title Smoke detection for static cameras
title_full Smoke detection for static cameras
title_fullStr Smoke detection for static cameras
title_full_unstemmed Smoke detection for static cameras
title_short Smoke detection for static cameras
title_sort Smoke detection for static cameras
topic Image color analysis
Cameras,
Image edge detection
Videos
Image resolution
Morphology
Probability
Image color analysis
Cameras,
Image edge detection
Videos
Image resolution
Morphology
Probability
url https://ieeexplore.ieee.org/abstract/document/7103719/
http://ridda2.utp.ac.pa/handle/123456789/5084