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计算机工程 ›› 2013, Vol. 39 ›› Issue (3): 279-284. doi: 10.3969/j.issn.1000-3428.2013.03.056

• 工程应用技术与实现 • 上一篇    下一篇

基于视频图像的远程火灾探测系统

胡 燕1a,1b,王慧琴1a,1b,张国飞1b,张小红1a,2,梁俊山1b   

  1. (1. 西安建筑科技大学 a. 管理学院;b. 信息与控制工程学院,西安 710055; 2. 西安科技大学通信与信息工程学院,西安 710044)
  • 收稿日期:2012-03-27 出版日期:2013-03-15 发布日期:2013-03-13
  • 作者简介:胡 燕(1981-),女,博士研究生,主研方向:信息安全,数字图像处理;王慧琴,教授、博士后、博士生导师;张国飞,硕士研究生;张小红,讲师、博士研究生;梁俊山,硕士研究生
  • 基金资助:
    陕西省科学技术研究发展计划基金资助项目(2011K17-04-01);西安市碑林区科技计划基金资助项目(GX1104); 西安建筑科技大学青年科技基金资助项目(QN1125)

Remote Fire Detection System Based on Video Image

HU Yan 1a,1b, WANG Hui-qin 1a,1b, ZHANG Guo-fei 1b, ZHANG Xiao-hong 1a,2, LIANG Jun-shan 1b   

  1. (1a. School of Management; 1b. School of Information and Control Engineering, Xi’an University of Architecture and Technology, Xi’an 710055, China; 2. School of Communication and Information Engineering, Xi’an University of Science and Technology, Xi’an 710044, China)
  • Received:2012-03-27 Online:2013-03-15 Published:2013-03-13

摘要: 将传感器技术用于大空间火灾探测时,存在距离短、误报率高、可靠性差等不足。为此,在TMS320DM642微处理器和TI的DSP/BIOS实时操作系统上,设计基于视频图像的远程火灾探测系统。建立RGB空间颜色模型,对连续数帧火灾图像做预处理,分析频闪特性并进行模糊聚类,提取疑似目标区域,以火焰相关性、面积变化率和圆形度3个特征作为火灾识别依据。实验结果表明,该系统提高了大空间图像型火灾探测的精度和速度,可满足远程火情监测需要。

关键词: 视频火灾探测, 颜色模型, 微处理器, 火焰特征, 模糊聚类, 嵌入式系统

Abstract: Remote fire detection system based on TMS320DM642 microprocessor and DSP/BIOS real-time operating system is implemented for resolving the probleme of detection shorter distance, higher misinformation and lower reliability of sensor technology in large space. Firstly a series of frames are pre-processed in RGB space. Then suspected target areas are extracted depending on the flickering feature and fuzzy clustering analysis. The features, such as fire correlation, rate of area growth and circularity are regarded recognization criterion of fire. DSP/BIOS and RF5 based-system is designed and tested to illuminate the scheme feasibility. Experimental result shows that the proposed system improves the accuracy and speed of image fire detection in a variety of large space, and it can meet the needs of remote fire detection.

Key words: video fire detection, color model, microprocessor, flame characteristic, fuzzy clustering, embedded system

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