Hyperspectral image-based Night-Time Fire Detection using NKNBD

被引:5
|
作者
Kim, Heekang [1 ]
Song, Chanho [1 ]
Son, Guk-Jin [1 ]
Jeong, Seong-Ho [1 ]
Son, Jin-Hwan [1 ]
Kim, Young-Duk [1 ]
机构
[1] DGIST, Daegu, South Korea
关键词
fire detection; hyperspectral image; nighttime;
D O I
10.1109/IIAI-AAI.2018.00208
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Fire detection on roads at night has many limitations in the fire detection technique using ordinary RGB cameras. It has the problem of misinterpretation of flame due to various lighting sources such as vehicle lighting (LED, halogen) and street lamp (LED, fluorescent lamp). Hyperspectral cameras have hundreds of bands that can distinguish light sources based on the spectra of the light source. Therefore, it is possible to distinguish between the light of the flame, the vehicle light on the road, and the light of the roadside tree. In this paper, a method to simulate a fire in an environment with vehicle lighting and streetlight and detect a fire using NKNBD (Normalized K and NIR Band Difference) in hyperspectral camera is discussed.
引用
收藏
页码:974 / 975
页数:2
相关论文
共 50 条
  • [41] Hyperspectral Image-Based Methods for Spectral Diversity
    Sotomayor, Alejandro
    Medina, Ollantay
    Chinea, J. Danilo
    Manian, Vidya
    ALGORITHMS AND TECHNOLOGIES FOR MULTISPECTRAL, HYPERSPECTRAL, AND ULTRASPECTRAL IMAGERY XXI, 2015, 9472
  • [42] Two-Step Real-Time Night-Time Fire Detection in an Urban Environment Using Static ELASTIC-YOLOv3 and Temporal Fire-Tube
    Park, MinJi
    Ko, Byoung Chul
    SENSORS, 2020, 20 (08)
  • [43] Automated image-based fire detection and alarm system using edge computing and cloud-based platform
    Yang, Xueliang
    Li, Yenchun
    Chen, Qian
    INTERNET OF THINGS, 2024, 28
  • [44] EFFICIENT AND REAL-TIME PEDESTRIAN DETECTION AT NIGHT-TIME ENVIRONMENTS
    Zhang, Yongjun
    Zhao, Yong
    Li, Guoliang
    Wei, Daimeng
    Cheng, Ruzhong
    INTERNATIONAL JOURNAL OF INNOVATIVE COMPUTING INFORMATION AND CONTROL, 2015, 11 (02): : 599 - 614
  • [45] Automated detection of impervious surfaces using night-time light and Landsat images based on an iterative classification framework
    Cheng, Xi
    Luo, Rui
    Shi, Guozhong
    Xia, Liegang
    Shen, Zhanfeng
    REMOTE SENSING LETTERS, 2020, 11 (05) : 465 - 474
  • [46] Image-based rendering using image-based priors
    Fitzgibbon, A
    Wexler, Y
    Zisserman, A
    INTERNATIONAL JOURNAL OF COMPUTER VISION, 2005, 63 (02) : 141 - 151
  • [47] Image-Based Rendering Using Image-Based Priors
    Andrew Fitzgibbon
    Yonatan Wexler
    Andrew Zisserman
    International Journal of Computer Vision, 2005, 63 : 141 - 151
  • [48] Image-based rendering using image-based priors
    Fitzgibbon, A
    Wexler, Y
    Zisserman, A
    NINTH IEEE INTERNATIONAL CONFERENCE ON COMPUTER VISION, VOLS I AND II, PROCEEDINGS, 2003, : 1176 - 1183
  • [49] Robust moving object detection using beam pattern for night-time driver assistance
    Zhang, Rui
    Park, Eunsoo
    Yun, Yongji
    Kim, Hakil
    Kim, Hyoungrae
    2012 IEEE 75TH VEHICULAR TECHNOLOGY CONFERENCE (VTC SPRING), 2012,
  • [50] Night-time cloud detection for FY-3A/VIRR using multispectral thresholds
    He, Quanjun
    INTERNATIONAL JOURNAL OF REMOTE SENSING, 2013, 34 (08) : 2876 - 2887