基于全方位视觉的火灾安全监控系统的研究
|
摘要
本文在图像获取手段上引入全方位视觉,在图像的分析、理解和信息加工上引入以人为中心的思想进行系统设计,利用计算机视觉技术,集动态图像理解和多特征信息融合于一体,对早期火灾的智能探测进行了探索,尝试实现一种能真正适用于大空间的图像型火灾安全监控系统。研究表明本文提出的系统能解决现有图像型火灾安全监控系统存在的监控范围小、实时处理差、实现算法复杂、对环境依赖性强等不足。
本文的主要工作和成果总结如下:
1.把实验室自主研发的全方位视觉传感器应用到火灾安全监控,并搭建嵌入式视频服务器,实现对大空间的实时全景监控。实现了全方位图的柱状全景图展开算法,使后续图像处理中的算法能够正确、方便的应用。
2.引入以人为中心的思想,利用动态图像语义理解的理论,设计了一种面向对象的火灾探测模型。该模型通过分析火焰对象的属性实现视频序列中火焰对象的识别,通过分析火焰对象的行为实现火焰燃烧模式的识别,并做出初步的火灾判断。为火灾安全监控系统的设计开发提供了一种新的思路。
3.研究普通CCD摄像头采集的视频序列中火焰目标对象的识别,详细介绍了在像素级使用运动、颜色和闪烁频率特征抽取火焰像素点,并实现了基于轮廓遍历的连通区域填充算法确定整个火焰区域,初步完成了具有语义信息的火焰目标对象的识别。
4.研究火焰面积增长、整体移动和边缘抖动等行为特征的量化分析算法,并应用模糊逻辑实现多特征融合,设计实现了基于模糊逻辑的火焰燃烧模式识别算法,把火焰的燃烧区分成环境中可能存在的可控燃烧和会引发火灾的失控燃烧两种模式,为早期火灾探测做好了充分的准备。
5.使用Java语言设计实现了火灾安全监控系统,实验了多种光照条件下的火灾安全监控,各种实验结果表明本文提出的大空间的火灾安全视频监控系统,具有监控范围大、实时处理好、实现算法精炼、对环境依赖性小等优点,通过多特征融合技术实现火灾判断的检测率有所提高,误检测率大大减少。
虽然本文对图像型火灾安全监控技术做了一些基础性的研究,但离图像型火灾探测的实际应用还有一定的距离,还有很多内容需要进一步的深入研究,希望本文的工作能够对后来的研究者起到一定的参考作用。
This paper introduced omni-directional vision to achieve a fire security system truly applicable to large space fire monitoring. According to the way people understanding the fire, this system used computer vision technology, combined with dynamic image understanding and multi-feature fusion, to implement intelligent fire detection. Experiments showed that this system could solve the shortcomings of existing vision based fire security system, such as poor real-time processing, complex algorithm, dependent on environment, etc.
The main work and the results were summarized as following:
1. Introduced omni-directional vision sensor to the fire security system, and structured embedded video server to achieve real-time panorama monitoring of large space. Developed unwrap algorithm to get panoramic image from omni-image, which was much better human readable and could be used properly in subsequent image processing.
2. Designed an object-oriented fire detection model based on dynamic image understanding theory. This model achieved flame recognition by analyzing the properties, understood flame combustion pattern by analyzing the behavior, judged fire based on these information. This approach provided a new way on designing an intelligent fire security system.
3. Researched on flame recognition of video sequence acquired by ordinary color camera. Detailed fire pixels extraction in the use of movement, color and frequency features. Designed and implemented the connected component filling algorithm based on contour traversal to identify the flame target region with semantic information.
4. Researched on quantitative analysis algorithm of flame behaviors such as area changes, overall spread and contour characteristics. Applied fuzzy logic to achieve multi-feature fusion, and then designed the flame combustion pattern recognition algorithm which divided it into two different patterns: controlled combustion pattern and out of control fire burning pattern.
5. Designed and implemented the fire security system using Java programming language. Performed a variety of experiments under different conditions of illumination, and achieved good experimental results. It showed that multi-feature fusion technology could increase the fire detection rate significantly.
Although this paper has done some basic research on vision based fire security technology, there is still a certain distance to the practical application of fire detection. Hope this work would be able to play a certain role in the reference to the further researchers on the same topic.
本文的主要工作和成果总结如下:
1.把实验室自主研发的全方位视觉传感器应用到火灾安全监控,并搭建嵌入式视频服务器,实现对大空间的实时全景监控。实现了全方位图的柱状全景图展开算法,使后续图像处理中的算法能够正确、方便的应用。
2.引入以人为中心的思想,利用动态图像语义理解的理论,设计了一种面向对象的火灾探测模型。该模型通过分析火焰对象的属性实现视频序列中火焰对象的识别,通过分析火焰对象的行为实现火焰燃烧模式的识别,并做出初步的火灾判断。为火灾安全监控系统的设计开发提供了一种新的思路。
3.研究普通CCD摄像头采集的视频序列中火焰目标对象的识别,详细介绍了在像素级使用运动、颜色和闪烁频率特征抽取火焰像素点,并实现了基于轮廓遍历的连通区域填充算法确定整个火焰区域,初步完成了具有语义信息的火焰目标对象的识别。
4.研究火焰面积增长、整体移动和边缘抖动等行为特征的量化分析算法,并应用模糊逻辑实现多特征融合,设计实现了基于模糊逻辑的火焰燃烧模式识别算法,把火焰的燃烧区分成环境中可能存在的可控燃烧和会引发火灾的失控燃烧两种模式,为早期火灾探测做好了充分的准备。
5.使用Java语言设计实现了火灾安全监控系统,实验了多种光照条件下的火灾安全监控,各种实验结果表明本文提出的大空间的火灾安全视频监控系统,具有监控范围大、实时处理好、实现算法精炼、对环境依赖性小等优点,通过多特征融合技术实现火灾判断的检测率有所提高,误检测率大大减少。
虽然本文对图像型火灾安全监控技术做了一些基础性的研究,但离图像型火灾探测的实际应用还有一定的距离,还有很多内容需要进一步的深入研究,希望本文的工作能够对后来的研究者起到一定的参考作用。
This paper introduced omni-directional vision to achieve a fire security system truly applicable to large space fire monitoring. According to the way people understanding the fire, this system used computer vision technology, combined with dynamic image understanding and multi-feature fusion, to implement intelligent fire detection. Experiments showed that this system could solve the shortcomings of existing vision based fire security system, such as poor real-time processing, complex algorithm, dependent on environment, etc.
The main work and the results were summarized as following:
1. Introduced omni-directional vision sensor to the fire security system, and structured embedded video server to achieve real-time panorama monitoring of large space. Developed unwrap algorithm to get panoramic image from omni-image, which was much better human readable and could be used properly in subsequent image processing.
2. Designed an object-oriented fire detection model based on dynamic image understanding theory. This model achieved flame recognition by analyzing the properties, understood flame combustion pattern by analyzing the behavior, judged fire based on these information. This approach provided a new way on designing an intelligent fire security system.
3. Researched on flame recognition of video sequence acquired by ordinary color camera. Detailed fire pixels extraction in the use of movement, color and frequency features. Designed and implemented the connected component filling algorithm based on contour traversal to identify the flame target region with semantic information.
4. Researched on quantitative analysis algorithm of flame behaviors such as area changes, overall spread and contour characteristics. Applied fuzzy logic to achieve multi-feature fusion, and then designed the flame combustion pattern recognition algorithm which divided it into two different patterns: controlled combustion pattern and out of control fire burning pattern.
5. Designed and implemented the fire security system using Java programming language. Performed a variety of experiments under different conditions of illumination, and achieved good experimental results. It showed that multi-feature fusion technology could increase the fire detection rate significantly.
Although this paper has done some basic research on vision based fire security technology, there is still a certain distance to the practical application of fire detection. Hope this work would be able to play a certain role in the reference to the further researchers on the same topic.
引文
[1]联合国火灾统计数据[OL].http://www.jhykj.cn/support/articles/fire%20damage.pdf.
[2]中国公安部火灾信息[OL].http://www.119.en/hzxx/node_503448.htm.
[3]吴龙标,方俊,谢启源.火灾探测与信息处理[M].北京:化学工业出版社,2006.
[4]陈涛,袁宏永,范维澄.火灾探测技术研究的展望[J].火灾科学,2001,10(2):108-112.
[5]帅师.基于视频的早期火灾烟雾及其发生源的检测研究[D].浙江理工大学硕士学位论文,2007.
[6]陈莹.大空间图像型火灾探测和自动灭火技术的研究[D].天津大学硕士学位论文,2006.
[7]刘亮亮.基于视频监控的火灾识别图像研究[D].华北电力大学硕士学位论文,2007.
[8]李力.中国火灾探测技术的现状及其发展趋势[J].火灾科学,2001,10(2):116-119.
[9]贺玉凯,关中辉.火灾探测技术发展趋势[J].辽宁工学院学报,2004,24(6):11-14.
[10]徐琼,詹福如,苏国锋,袁宏永.火灾烟雾探测技术的发展与探讨[J].火灾科学,2002,11(2):113-118.
[11]袁宏永,赵建华,苏国锋.图像型大空间建筑早期火灾智能探测报警技术[J].消防技术与产品信息,2001,(2):30-32.
[12]疏学明,苏国锋,袁宏永,邵荃.基于光散射的火灾烟雾粒子激光图像探测技术研究[J].光散射学报,2004,16(3):237-241.
[13]崔凯,曹榆,冯杰平.图像型火灾探测技术浅析[J].消防技术与产品信息,2005,(4):30-32.
[14]张田莉.视频感烟探测系统为世界最大的飞机维修库护航[J].消防技术与产品信息,2007,(3):52-54.
[15]安志伟.图像型火灾监控技术若干问题的研究[D].中国科技大学硕士学位论文,2000.
[16]马新,曹希锋.红外技术在早期火灾探测中的应用[J].消防技术与产品信息,2003,(10):19-22.
[17]郑英,张万宝,陈惠明.森林火灾地面红外探测技术的研究[J].森林防火,2006,(4):28-30.
[18]李明,吴爱国.大空间早期火灾的双波段图像型探测方法[J].消防与安全,2007,(2):37-40.
[19]孙宇臣,王自朝,葛宝臻.视频火灾探测系统现状分析[J].消防科学与技术,2007,26(4):414-417.
[20]Healey G,Slater D,Lin T,Drda B,Goedeke A D.A System for Real-Time Fire Detection[A].IEEE Computer Society Conference on Computer Vision and Pattern Recognition[C].New York:1993,605-606.
[21]Phillips W Ⅲ,Shah M,Da Vitoria Lobo N.Flame Recognition in Video[A].Fifth IEEE workshop on Applications of Computer Vision[C].Palm Springs:2000,224-229.
[22]Kjedlsen R,Kender J.Finding Skin in Color Images[A].Proceedings of the Second Intemational Conference on Automatic Face and Gesture Recognition[C].Killington:1996,312-317.
[23]Chen T H,Kao C L,Chang S M.An intelligent real-time fire-detection method based on video processing[A].Proceedings of IEEE 37th Annual 2003 Intemational Carnahan Conference on Security Technology[C].Taiwan:2003,104-111.
[24]Chen T H,Wu P H,Chiou Y C.An early fire-detection method based on image processing[A].Proceedings of 2004 International Conference on Image Processing[C].Singapore:2004,1707-1710.
[25]Chen T H,Yin Y Y,Ye Y Y.A Cost-Effective Early Fire-Alarming System Based on Video Processing [OL].www.csie.stut.edu.tw/dspcdc2006/CD_Eng/pdf/10Taiwan.pdf.
[26]Yuan F N,Liao G X,Fan W C,Zhou H Q.Vision Based Fire Detection Using Mixture Gaussian Model[A].8th International Symposium on Fire Safety Science[C].2005.
[27]Celik T,Demirel H,Ozkaramanli H,Uyguroglu M.Fire Detection Using Statistical Color Model in Video Sequences[J].Journal of Visual Communication and Image Representation,2007,18(2):176-185.
[28]Elgammal A,Harwood D,Davis L S.Nonparametric background model for background subtraction [A].Proceedings of the 6th European Conference on Computer Vision-Part Ⅱ[C].London:Springer-Verlag,2000,751-767.
[29]Liu C B,Ahuja N.Vision based fire detection[A].Proceedings of IEEE 17th International Conference on Pattern Recognition[C].2004,134-137.
[30]Persoon E,Fu K.Shape discrimination using fourier descriptors[J].IEEE Transactions on Pattern Analysis and Machine Intelligence,1986,8(3):388-397.
[31]袁非牛,廖光煊,张永明,刘勇,于春雨,王进军,刘炳海.计算机视觉火灾探测中的特征提取[J].中国科学技术大学学报,2006,36(1):39-43.
[32]Toreyin B U,Dedeoglu Y,Gudukbay U,Cetin A E.Computer Vision Based Method for Real-time Fire and Flame Detection[J].Short Communication Pattern Recognition Letters,2006,27(1):49-58.
[33]Dedeoglu Y,Toreyin B U,Gudukbay U,Cetin A E.Real-time Fire and Flame Detection in Video[A].Proceedings of International Conference on Acoustics,Speech,and Signal Processing[C].2005,669-672.
[34]Toreyin B U,Dedeoglu Y,Cetin A E.Flame Detection in Video using Hidden Markov Models[A].IEEE International Conference on Image Processing[C].2005.
[35]Yamagishi H,Yamaguehi J.Fire Flame Detection Algorithm Using a Color Camera[A].Proceedings of 1999 International Symposium on Mieromechatronics and Human Science[C].1999,255-260.
[36]Yamagishi H,Yamaguchi J.A Contour Fluctuation Data Processing Method For Fire Flame Detection Using A Color Camera[A].Proceedings of the 26th Annual Conference of the IEEE Industrial Electronics Society[C].2000,824-829.
[37]卢结成,吴龙标,宋卫国.一种火灾图像探测系统的研究[J].仪器仪表学报,2001,22(4):437-440.
[38]楼建光.路面车辆运动的语义理解[D].北京:中国科学院,2003.
[39]石跃祥.图像与语义[D].中南大学博士学位论文,2005.
[40]张进华,庄健,杜海峰,王孙安.一种基于视频多特征融合的火焰识别算法[J].西安交通大学学报,2006,40(7):811-814.
[41]Zhang J H,Zhuang J,Du H F,Wang S A,Li X H.A Flame Detection Algorithm Based on Video Multi-feature Fusion[J].Lecture Notes in Computer Science,2006,4222:784-792.
[42]Simon Y.Foo.A Fuzzy Logic Approach to Fire Detection in Aircraft Dry Bays and Engine Compartments [J].IEEE Transactions on Industrial Electronics,2000,47(5):1161-1171.
[43]D.Rees.Panoramic Television Viewing System[P].United States Patent:3505465,1970.
[44]汤一平,叶永杰,朱艺华,顾校凯.智能全方位视觉传感器及其应用研究[J].传感技术学报,2007,20(6):1316-1320.
[45]皮文凯.基于全方位视觉的人体运动检测和跟踪[D].北京大学硕士学位论文,2004.
[46]陈焱,杨东勇,沈正伟.全方位图像展开成全景和透视图的实现方法[J].计算机工程,2007,33(2):183-185.
[47]Babaguchi N,Fujimoto Y,Yamazawa K,et al.A System for Visualization and Summarization of Omnidirectional Surveillance Video[A].Proceedings of the 8th International WorkShop on Multimedia Information System[C].Tempe:2002,18-27.
[48]Stauffer C,Grimson W E L.Adaptive background mixture models for real time tracking[A].IEEE Computer Society Conference on Computer Vision and Pattern Recognition[C].Fort Collins:1999.
[49]Power W P,Schoonees J A.Understanding Background Mixture Models for Foreground Segmentation [A].Proceedings Image and Vision Computing New Zealand[C].2002.
[50]The HIS color space[OL].http://www.blackice.com/images/HSIColorModel.jpg.
[51]安志伟,袁宏永,屈玉贵.数据采集在火焰闪烁频率的测量研究及分析中的应用[J].火灾科学,2000,9(2):43-47.
[52]吕普轶.基于普通CCD摄像机的火灾探测技术的研究[D].哈尔滨工程大学硕士学位论文,2003.
[53]宋文忠,姜昌金,胡克定.锅炉燃烧器火焰闪烁特性试验与分析[J].热力发电,1995,(4):45-51.
[54]郎锐.数字图像处理学-Visual C++实现[M].北京:北京希望电子出版社,2003.
[55]张志龙,李吉成,沈振康.一种新的快速复杂连通区域扫描线填充算法[J].计算机工程与应用,2004,(31):6-8.
[56]Zhang D S,Lu G.A Comparative Study on Shape Retrieval Using Fourier Descriptors with Different Shape Signatures[A].Proceedings of the International Conference on Multimedia and Distance Education[C].Fargo:2001,1-9.
[57]陈晓娟,卜乐平,李其修.基于图像处理的明火火灾探测研究[J].海军工程大学学报,2007,19(3):6-11.
[58]杨继华,严国萍.基于嵌入式Linux与S3C2410平台的视频采集[J].单片机与嵌入式系统应用,2004,11(1):69-71.
[2]中国公安部火灾信息[OL].http://www.119.en/hzxx/node_503448.htm.
[3]吴龙标,方俊,谢启源.火灾探测与信息处理[M].北京:化学工业出版社,2006.
[4]陈涛,袁宏永,范维澄.火灾探测技术研究的展望[J].火灾科学,2001,10(2):108-112.
[5]帅师.基于视频的早期火灾烟雾及其发生源的检测研究[D].浙江理工大学硕士学位论文,2007.
[6]陈莹.大空间图像型火灾探测和自动灭火技术的研究[D].天津大学硕士学位论文,2006.
[7]刘亮亮.基于视频监控的火灾识别图像研究[D].华北电力大学硕士学位论文,2007.
[8]李力.中国火灾探测技术的现状及其发展趋势[J].火灾科学,2001,10(2):116-119.
[9]贺玉凯,关中辉.火灾探测技术发展趋势[J].辽宁工学院学报,2004,24(6):11-14.
[10]徐琼,詹福如,苏国锋,袁宏永.火灾烟雾探测技术的发展与探讨[J].火灾科学,2002,11(2):113-118.
[11]袁宏永,赵建华,苏国锋.图像型大空间建筑早期火灾智能探测报警技术[J].消防技术与产品信息,2001,(2):30-32.
[12]疏学明,苏国锋,袁宏永,邵荃.基于光散射的火灾烟雾粒子激光图像探测技术研究[J].光散射学报,2004,16(3):237-241.
[13]崔凯,曹榆,冯杰平.图像型火灾探测技术浅析[J].消防技术与产品信息,2005,(4):30-32.
[14]张田莉.视频感烟探测系统为世界最大的飞机维修库护航[J].消防技术与产品信息,2007,(3):52-54.
[15]安志伟.图像型火灾监控技术若干问题的研究[D].中国科技大学硕士学位论文,2000.
[16]马新,曹希锋.红外技术在早期火灾探测中的应用[J].消防技术与产品信息,2003,(10):19-22.
[17]郑英,张万宝,陈惠明.森林火灾地面红外探测技术的研究[J].森林防火,2006,(4):28-30.
[18]李明,吴爱国.大空间早期火灾的双波段图像型探测方法[J].消防与安全,2007,(2):37-40.
[19]孙宇臣,王自朝,葛宝臻.视频火灾探测系统现状分析[J].消防科学与技术,2007,26(4):414-417.
[20]Healey G,Slater D,Lin T,Drda B,Goedeke A D.A System for Real-Time Fire Detection[A].IEEE Computer Society Conference on Computer Vision and Pattern Recognition[C].New York:1993,605-606.
[21]Phillips W Ⅲ,Shah M,Da Vitoria Lobo N.Flame Recognition in Video[A].Fifth IEEE workshop on Applications of Computer Vision[C].Palm Springs:2000,224-229.
[22]Kjedlsen R,Kender J.Finding Skin in Color Images[A].Proceedings of the Second Intemational Conference on Automatic Face and Gesture Recognition[C].Killington:1996,312-317.
[23]Chen T H,Kao C L,Chang S M.An intelligent real-time fire-detection method based on video processing[A].Proceedings of IEEE 37th Annual 2003 Intemational Carnahan Conference on Security Technology[C].Taiwan:2003,104-111.
[24]Chen T H,Wu P H,Chiou Y C.An early fire-detection method based on image processing[A].Proceedings of 2004 International Conference on Image Processing[C].Singapore:2004,1707-1710.
[25]Chen T H,Yin Y Y,Ye Y Y.A Cost-Effective Early Fire-Alarming System Based on Video Processing [OL].www.csie.stut.edu.tw/dspcdc2006/CD_Eng/pdf/10Taiwan.pdf.
[26]Yuan F N,Liao G X,Fan W C,Zhou H Q.Vision Based Fire Detection Using Mixture Gaussian Model[A].8th International Symposium on Fire Safety Science[C].2005.
[27]Celik T,Demirel H,Ozkaramanli H,Uyguroglu M.Fire Detection Using Statistical Color Model in Video Sequences[J].Journal of Visual Communication and Image Representation,2007,18(2):176-185.
[28]Elgammal A,Harwood D,Davis L S.Nonparametric background model for background subtraction [A].Proceedings of the 6th European Conference on Computer Vision-Part Ⅱ[C].London:Springer-Verlag,2000,751-767.
[29]Liu C B,Ahuja N.Vision based fire detection[A].Proceedings of IEEE 17th International Conference on Pattern Recognition[C].2004,134-137.
[30]Persoon E,Fu K.Shape discrimination using fourier descriptors[J].IEEE Transactions on Pattern Analysis and Machine Intelligence,1986,8(3):388-397.
[31]袁非牛,廖光煊,张永明,刘勇,于春雨,王进军,刘炳海.计算机视觉火灾探测中的特征提取[J].中国科学技术大学学报,2006,36(1):39-43.
[32]Toreyin B U,Dedeoglu Y,Gudukbay U,Cetin A E.Computer Vision Based Method for Real-time Fire and Flame Detection[J].Short Communication Pattern Recognition Letters,2006,27(1):49-58.
[33]Dedeoglu Y,Toreyin B U,Gudukbay U,Cetin A E.Real-time Fire and Flame Detection in Video[A].Proceedings of International Conference on Acoustics,Speech,and Signal Processing[C].2005,669-672.
[34]Toreyin B U,Dedeoglu Y,Cetin A E.Flame Detection in Video using Hidden Markov Models[A].IEEE International Conference on Image Processing[C].2005.
[35]Yamagishi H,Yamaguehi J.Fire Flame Detection Algorithm Using a Color Camera[A].Proceedings of 1999 International Symposium on Mieromechatronics and Human Science[C].1999,255-260.
[36]Yamagishi H,Yamaguchi J.A Contour Fluctuation Data Processing Method For Fire Flame Detection Using A Color Camera[A].Proceedings of the 26th Annual Conference of the IEEE Industrial Electronics Society[C].2000,824-829.
[37]卢结成,吴龙标,宋卫国.一种火灾图像探测系统的研究[J].仪器仪表学报,2001,22(4):437-440.
[38]楼建光.路面车辆运动的语义理解[D].北京:中国科学院,2003.
[39]石跃祥.图像与语义[D].中南大学博士学位论文,2005.
[40]张进华,庄健,杜海峰,王孙安.一种基于视频多特征融合的火焰识别算法[J].西安交通大学学报,2006,40(7):811-814.
[41]Zhang J H,Zhuang J,Du H F,Wang S A,Li X H.A Flame Detection Algorithm Based on Video Multi-feature Fusion[J].Lecture Notes in Computer Science,2006,4222:784-792.
[42]Simon Y.Foo.A Fuzzy Logic Approach to Fire Detection in Aircraft Dry Bays and Engine Compartments [J].IEEE Transactions on Industrial Electronics,2000,47(5):1161-1171.
[43]D.Rees.Panoramic Television Viewing System[P].United States Patent:3505465,1970.
[44]汤一平,叶永杰,朱艺华,顾校凯.智能全方位视觉传感器及其应用研究[J].传感技术学报,2007,20(6):1316-1320.
[45]皮文凯.基于全方位视觉的人体运动检测和跟踪[D].北京大学硕士学位论文,2004.
[46]陈焱,杨东勇,沈正伟.全方位图像展开成全景和透视图的实现方法[J].计算机工程,2007,33(2):183-185.
[47]Babaguchi N,Fujimoto Y,Yamazawa K,et al.A System for Visualization and Summarization of Omnidirectional Surveillance Video[A].Proceedings of the 8th International WorkShop on Multimedia Information System[C].Tempe:2002,18-27.
[48]Stauffer C,Grimson W E L.Adaptive background mixture models for real time tracking[A].IEEE Computer Society Conference on Computer Vision and Pattern Recognition[C].Fort Collins:1999.
[49]Power W P,Schoonees J A.Understanding Background Mixture Models for Foreground Segmentation [A].Proceedings Image and Vision Computing New Zealand[C].2002.
[50]The HIS color space[OL].http://www.blackice.com/images/HSIColorModel.jpg.
[51]安志伟,袁宏永,屈玉贵.数据采集在火焰闪烁频率的测量研究及分析中的应用[J].火灾科学,2000,9(2):43-47.
[52]吕普轶.基于普通CCD摄像机的火灾探测技术的研究[D].哈尔滨工程大学硕士学位论文,2003.
[53]宋文忠,姜昌金,胡克定.锅炉燃烧器火焰闪烁特性试验与分析[J].热力发电,1995,(4):45-51.
[54]郎锐.数字图像处理学-Visual C++实现[M].北京:北京希望电子出版社,2003.
[55]张志龙,李吉成,沈振康.一种新的快速复杂连通区域扫描线填充算法[J].计算机工程与应用,2004,(31):6-8.
[56]Zhang D S,Lu G.A Comparative Study on Shape Retrieval Using Fourier Descriptors with Different Shape Signatures[A].Proceedings of the International Conference on Multimedia and Distance Education[C].Fargo:2001,1-9.
[57]陈晓娟,卜乐平,李其修.基于图像处理的明火火灾探测研究[J].海军工程大学学报,2007,19(3):6-11.
[58]杨继华,严国萍.基于嵌入式Linux与S3C2410平台的视频采集[J].单片机与嵌入式系统应用,2004,11(1):69-71.