林火图像识别理论研究进展

编号 lyqk006472

中文标题 林火图像识别理论研究进展

作者 袁雯雯  姜树海 

作者单位 南京林业大学智能控制与机器人技术研究所,南京 210037;南京林业大学机械电子工程学院,南京 210037,南京林业大学智能控制与机器人技术研究所,南京 210037;南京林业大学机械电子工程学院,南京 210037

期刊名称 世界林业研究 

年份 2018 

卷号 31

期号 1

栏目编号 1

栏目名称 专题论述 

中文摘要 林火图像识别理论与方法是实现森林火灾视频自动监测的基础。文中从图像预处理、图像分割和特征提取3个方面详细地综述了国内外林火图像识别理论的发展现状，分析了图像颜色处理、图像滤波、图像阈值分割、区域分割、边缘分割以及动静态特征提取理论在林火图像识别应用中的优缺点；针对目前林火图像识别理论研究现状，指出在未来研究中需要解决的问题以及林火图像识别理论的发展方向，以期为图像识别技术在林火图像识别中的应用和进一步研究提供参考。

关键词 森林火灾  图像识别  图像预处理  图像分割  特征提取 

基金项目 国家公益性行业科研专项重大项目（201404402-03）。

英文标题 Research Progress in Forest Fire Image Recognition Theory

作者英文名 Yuan Wenwen and Jiang Shuhai

单位英文名 Institute of Intelligent Control and Robotics,Nanjing Forestry University,Nanjing 210037,China;College of Mechanical and Electronic Engineering,Nanjing Forestry University,Nanjing 210037,China and Institute of Intelligent Control and Robotics,Nanjing Forestry University,Nanjing 210037,China;College of Mechanical and Electronic Engineering,Nanjing Forestry University,Nanjing 210037,China

英文摘要 The theory and method of forest fire image recognition is the basis to achieve the automatic monitoring of forest fire video. This paper summarized in detail the development of forest fire image recognition theory at home and abroad in terms of image preprocessing, image segmentation and feature extraction. It also analyzed the advantages and disadvantages of image color processing, image filtering, image threshold segmentation, region segmentation, edge segmentation and dynamic and static feature extraction theory. In view of the current research on forest fire image recognition theory, the paper put forward the problems that need to be solved in the future research on forest fire image recognition theory, and pointed out its future development direction. This study is expected to provide references to the application of image recognition technology to the forest fire image recognition as well as the further research in this regard.

英文关键词 forest fire;image recognition;image preprocessing;image segmentation;feature extraction

起始页码 35

截止页码 39

投稿时间 2017/6/8

分类号 S762.3+2;TP751

DOI 10.13348/j.cnki.sjlyyj.2017.0079.y

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