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计算机科学与应用
Vol. 6 No. 3 (March 2016)
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基于视频图像的火焰检测
Flame Detection Based on Video
DOI:
10.12677/CSA.2016.63021
,
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作者:
李凯
,
李生波
,
刘瑞
,
王杰
,
刘丹
:淮阴工学院计算机工程学院,江苏 淮安
关键词:
火焰检测
;
背景差分
;
颜色特征
;
形状特征
;
Fire Detection
;
Background Subtraction
;
Color Feature
;
Shape Feature
摘要:
火灾是当今生活中十分常见的自然灾害,因此及时检测火焰对预防火灾的发生十分重要。本文提出了一种基于背景差分和颜色、形状特征的火焰检测方法。该算法首先采用背景差分法,根据火焰燃烧的动态性实现对运动目标的提取,再根据火焰颜色特征的五条规则以及火焰的三个形状特征对目标区域进一步提取,得到最终的检测结果。该方法火焰检测率较高,具有较好的实用价值。
Abstract:
Fire as a natural disaster is very common in our life. Therefore, flame detection timely is very im-portant for the prevention of fire. In this paper, a novel fire detection method is proposed based on background subtraction, color feature and shape features. Firstly, the moving object is extracted with background image difference based on the dynamic feature of fire. Then, the target areas are extracted exactly by five rules of color feature and three shape features of fire. Finally, the suspected flame is detected. The proposed method shows more effective for fire detection and presents high use value.
文章引用:
李凯, 李生波, 刘瑞, 王杰, 刘丹. 基于视频图像的火焰检测[J]. 计算机科学与应用, 2016, 6(3): 171-177.
http://dx.doi.org/10.12677/CSA.2016.63021
参考文献
[
1
]
范一舟, 马洪兵. 基于视频的林火烟雾识别方法[J]. 清华大学学报, 2015, 55(2): 243-256.
[
2
]
Chen, T.H., Wu, P.H. and Chiou, Y.C. (2004) An Early Fire-Detection Method Based on Image Processing. International Conference on Image Processing (ICIP), Taiwan, 24-27 October 2004, 1707-1710.
[
3
]
Toreyin, B.U., Dedeoglu, Y. and Cetin, A.E. (2005) Flame Detection in Video Using Hidden Markov Models. Proceedings of IEEE International Conference on Image Processing, 2, 1230-1233.
[
4
]
王莹, 李文辉. 基于多特征融合的高精度视频火焰检测算法[J]. 吉林大学学报: 工学版, 2010, 40(3): 769-775.
[
5
]
Wirth, M. and Zaremba, R. (2010) Flame Region Detection Based on Histogram Back Projection. 2010 Canadian Conference on Computer and Robot Vision (CRV), Ottawa, 31 May 2010-2 June 2010, 167-174.
[
6
]
Horng, W.B., Peng, J.W. and Chen, C.Y. (2005) A New Image-Based Real-Time Flame Detection Method Using Color Analysis. Proceedings of 2005 IEEE International Conference on Networking, Sensing and Control, Tucson, 19-22 March 2005, 100-105.
[
7
]
Habiboglu, Y.H., Günay, O. and Cetin, A.E. (2012) Covariance Matrix-Based Fire and Flame Detection Method in Video. Machine Vision and Applications, 23, 1103-1113.
http://dx.doi.org/10.1007/s00138-011-0369-1
[
8
]
Li, Y.-C. and Wu, W. (2011) Visual Fire Detection Based on Data Mining Technique. 2011 1st International Conference on Robot. Vision and Signal Processing, 11, 238-331.
[
9
]
Jenifer, P. (2011) Effective Visual Fire Detection in Video Sequences Using Probabilistic Approach. 2011 International Conference on Emerging Trends in Electrical and Computer Technology (ICETECT), Nagercoil, 23-24 March 2011, 870-875.
[
10
]
于成中, 朱骏, 袁晓辉. 基于背景差法的运动目标检测[J]. 东南大学学报, 2005, 35(2): 47-52.
[
11
]
吴茜茵, 严云洋, 杜静, 等. 多特征融合的火焰检测算法[J]. 智能系统学报, 2015(2): 240-247.
[
12
]
Yang, X., Wang, J. and He, S. (2012) A SVM Approach for Vessel Fire Detection Based on Image Processing. Proceedings of IEEE International Conference on Modeling, Identification & Control (ICMIC), Wuhan, 24-26 June 2012, 150-153.
[
13
]
丘兆文, 张田文. 一种新的图像颜色特征提取方法[J]. 哈尔滨工业大学学报, 2004, 36(12): 1699-1701.
[
14
]
荣建忠, 姚卫. 基于多特征融合技术的火焰视频探测方法[J]. 燃烧科学与技术, 2013, 19(3): 227-233.
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