Candidate Smoke Region Segmentation of Fire Video Based on Rough Set Theory
Candidate smoke region segmentation is the key link of smoke video detection; an effective and prompt method of candidate smoke region segmentation plays a significant role in a smoke recognition system. However, the interference of heavy fog and smoke-color moving objects greatly degrades the recog...
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| Format: | Article |
| Language: | English |
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Wiley
2015-01-01
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| Series: | Journal of Electrical and Computer Engineering |
| Online Access: | http://dx.doi.org/10.1155/2015/280415 |
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| _version_ | 1832561214550441984 |
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| author | Yaqin Zhao |
| author_facet | Yaqin Zhao |
| author_sort | Yaqin Zhao |
| collection | DOAJ |
| description | Candidate smoke region segmentation is the key link of smoke video detection; an effective and prompt method of candidate smoke region segmentation plays a significant role in a smoke recognition system. However, the interference of heavy fog and smoke-color moving objects greatly degrades the recognition accuracy. In this paper, a novel method of candidate smoke region segmentation based on rough set theory is presented. First, Kalman filtering is used to update video background in order to exclude the interference of static smoke-color objects, such as blue sky. Second, in RGB color space smoke regions are segmented by defining the upper approximation, lower approximation, and roughness of smoke-color distribution. Finally, in HSV color space small smoke regions are merged by the definition of equivalence relation so as to distinguish smoke images from heavy fog images in terms of V component value variety from center to edge of smoke region. The experimental results on smoke region segmentation demonstrated the effectiveness and usefulness of the proposed scheme. |
| format | Article |
| id | doaj-art-51386a6406fa409a88cab192041f41e3 |
| institution | Kabale University |
| issn | 2090-0147 2090-0155 |
| language | English |
| publishDate | 2015-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Journal of Electrical and Computer Engineering |
| spelling | doaj-art-51386a6406fa409a88cab192041f41e32025-02-03T01:25:42ZengWileyJournal of Electrical and Computer Engineering2090-01472090-01552015-01-01201510.1155/2015/280415280415Candidate Smoke Region Segmentation of Fire Video Based on Rough Set TheoryYaqin Zhao0College of Mechanical and Electronic Engineering, Nanjing Forestry University, Nanjing 210037, ChinaCandidate smoke region segmentation is the key link of smoke video detection; an effective and prompt method of candidate smoke region segmentation plays a significant role in a smoke recognition system. However, the interference of heavy fog and smoke-color moving objects greatly degrades the recognition accuracy. In this paper, a novel method of candidate smoke region segmentation based on rough set theory is presented. First, Kalman filtering is used to update video background in order to exclude the interference of static smoke-color objects, such as blue sky. Second, in RGB color space smoke regions are segmented by defining the upper approximation, lower approximation, and roughness of smoke-color distribution. Finally, in HSV color space small smoke regions are merged by the definition of equivalence relation so as to distinguish smoke images from heavy fog images in terms of V component value variety from center to edge of smoke region. The experimental results on smoke region segmentation demonstrated the effectiveness and usefulness of the proposed scheme.http://dx.doi.org/10.1155/2015/280415 |
| spellingShingle | Yaqin Zhao Candidate Smoke Region Segmentation of Fire Video Based on Rough Set Theory Journal of Electrical and Computer Engineering |
| title | Candidate Smoke Region Segmentation of Fire Video Based on Rough Set Theory |
| title_full | Candidate Smoke Region Segmentation of Fire Video Based on Rough Set Theory |
| title_fullStr | Candidate Smoke Region Segmentation of Fire Video Based on Rough Set Theory |
| title_full_unstemmed | Candidate Smoke Region Segmentation of Fire Video Based on Rough Set Theory |
| title_short | Candidate Smoke Region Segmentation of Fire Video Based on Rough Set Theory |
| title_sort | candidate smoke region segmentation of fire video based on rough set theory |
| url | http://dx.doi.org/10.1155/2015/280415 |
| work_keys_str_mv | AT yaqinzhao candidatesmokeregionsegmentationoffirevideobasedonroughsettheory |