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An Early Fire Detection Algorithm Using IP Cameras
The presence of smoke is the first symptom of fire; therefore to achieve early fire detection, accurate and quick estimation of the presence of smoke is very important. In this paper we propose an algorithm to detect the presence of smoke using video sequences captured by Internet Protocol (IP) came...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Molecular Diversity Preservation International (MDPI)
2012
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3386706/ https://www.ncbi.nlm.nih.gov/pubmed/22778607 http://dx.doi.org/10.3390/s120505670 |
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author | Millan-Garcia, Leonardo Sanchez-Perez, Gabriel Nakano, Mariko Toscano-Medina, Karina Perez-Meana, Hector Rojas-Cardenas, Luis |
author_facet | Millan-Garcia, Leonardo Sanchez-Perez, Gabriel Nakano, Mariko Toscano-Medina, Karina Perez-Meana, Hector Rojas-Cardenas, Luis |
author_sort | Millan-Garcia, Leonardo |
collection | PubMed |
description | The presence of smoke is the first symptom of fire; therefore to achieve early fire detection, accurate and quick estimation of the presence of smoke is very important. In this paper we propose an algorithm to detect the presence of smoke using video sequences captured by Internet Protocol (IP) cameras, in which important features of smoke, such as color, motion and growth properties are employed. For an efficient smoke detection in the IP camera platform, a detection algorithm must operate directly in the Discrete Cosine Transform (DCT) domain to reduce computational cost, avoiding a complete decoding process required for algorithms that operate in spatial domain. In the proposed algorithm the DCT Inter-transformation technique is used to increase the detection accuracy without inverse DCT operation. In the proposed scheme, firstly the candidate smoke regions are estimated using motion and color smoke properties; next using morphological operations the noise is reduced. Finally the growth properties of the candidate smoke regions are furthermore analyzed through time using the connected component labeling technique. Evaluation results show that a feasible smoke detection method with false negative and false positive error rates approximately equal to 4% and 2%, respectively, is obtained. |
format | Online Article Text |
id | pubmed-3386706 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2012 |
publisher | Molecular Diversity Preservation International (MDPI) |
record_format | MEDLINE/PubMed |
spelling | pubmed-33867062012-07-09 An Early Fire Detection Algorithm Using IP Cameras Millan-Garcia, Leonardo Sanchez-Perez, Gabriel Nakano, Mariko Toscano-Medina, Karina Perez-Meana, Hector Rojas-Cardenas, Luis Sensors (Basel) Article The presence of smoke is the first symptom of fire; therefore to achieve early fire detection, accurate and quick estimation of the presence of smoke is very important. In this paper we propose an algorithm to detect the presence of smoke using video sequences captured by Internet Protocol (IP) cameras, in which important features of smoke, such as color, motion and growth properties are employed. For an efficient smoke detection in the IP camera platform, a detection algorithm must operate directly in the Discrete Cosine Transform (DCT) domain to reduce computational cost, avoiding a complete decoding process required for algorithms that operate in spatial domain. In the proposed algorithm the DCT Inter-transformation technique is used to increase the detection accuracy without inverse DCT operation. In the proposed scheme, firstly the candidate smoke regions are estimated using motion and color smoke properties; next using morphological operations the noise is reduced. Finally the growth properties of the candidate smoke regions are furthermore analyzed through time using the connected component labeling technique. Evaluation results show that a feasible smoke detection method with false negative and false positive error rates approximately equal to 4% and 2%, respectively, is obtained. Molecular Diversity Preservation International (MDPI) 2012-05-03 /pmc/articles/PMC3386706/ /pubmed/22778607 http://dx.doi.org/10.3390/s120505670 Text en © 2012 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 license (http://creativecommons.org/licenses/by/3.0/). |
spellingShingle | Article Millan-Garcia, Leonardo Sanchez-Perez, Gabriel Nakano, Mariko Toscano-Medina, Karina Perez-Meana, Hector Rojas-Cardenas, Luis An Early Fire Detection Algorithm Using IP Cameras |
title | An Early Fire Detection Algorithm Using IP Cameras |
title_full | An Early Fire Detection Algorithm Using IP Cameras |
title_fullStr | An Early Fire Detection Algorithm Using IP Cameras |
title_full_unstemmed | An Early Fire Detection Algorithm Using IP Cameras |
title_short | An Early Fire Detection Algorithm Using IP Cameras |
title_sort | early fire detection algorithm using ip cameras |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3386706/ https://www.ncbi.nlm.nih.gov/pubmed/22778607 http://dx.doi.org/10.3390/s120505670 |
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