Wildfire smoke detection using computational intelligence techniques

A. Genovese, R. D. Labati, V. Piuri, F. Scotti
{"title":"Wildfire smoke detection using computational intelligence techniques","authors":"A. Genovese, R. D. Labati, V. Piuri, F. Scotti","doi":"10.1109/CIMSA.2011.6059930","DOIUrl":null,"url":null,"abstract":"In this paper, we propose an image processing system for the detection of wildfire smoke based on computational intelligence techniques and capable of adapting to different applicative environments. The proposed system is designed for processing with limited computational complexity. The detection process focuses on the extraction of specific features of wildfire smoke. A computational intelligence classifier is adopted to identify the presence of smoke. In order to test its effectiveness, the proposed system has been tested with low quality frame sequences, providing the capability to deal also with low cost cameras. The results indicate that the proposed approach is accurate and can be effectively applied in different environmental conditions.","PeriodicalId":422972,"journal":{"name":"2011 IEEE International Conference on Computational Intelligence for Measurement Systems and Applications (CIMSA) Proceedings","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2011-10-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"38","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2011 IEEE International Conference on Computational Intelligence for Measurement Systems and Applications (CIMSA) Proceedings","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CIMSA.2011.6059930","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 38

Abstract

In this paper, we propose an image processing system for the detection of wildfire smoke based on computational intelligence techniques and capable of adapting to different applicative environments. The proposed system is designed for processing with limited computational complexity. The detection process focuses on the extraction of specific features of wildfire smoke. A computational intelligence classifier is adopted to identify the presence of smoke. In order to test its effectiveness, the proposed system has been tested with low quality frame sequences, providing the capability to deal also with low cost cameras. The results indicate that the proposed approach is accurate and can be effectively applied in different environmental conditions.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
利用计算智能技术进行野火烟雾探测
本文提出了一种基于计算智能技术的野火烟雾检测图像处理系统,该系统能够适应不同的应用环境。该系统设计用于计算复杂度有限的处理。检测过程的重点是提取野火烟雾的具体特征。采用计算智能分类器来识别烟雾的存在。为了验证其有效性,本文提出的系统已经在低质量的帧序列上进行了测试,提供了处理低成本摄像机的能力。结果表明,该方法具有较高的准确性,可有效地应用于不同的环境条件。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Personal dosimeter for the measurement of artificial optical radiation (AOR) exposure Designing a fuzzy expert system to predict the concrete mix design Wildfire smoke detection using computational intelligence techniques Low-cost optimal state feedback fuzzy control of nonlinear second-order servo systems Intelligent control of bioreactor landfills
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1