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Pattern Recognition and Image Analysis

, Volume 28, Issue 4, pp 805–812 | Cite as

Detection of Wildfires along Transmission Lines Using Deep Time and Space Features

  • Jie Yuan
  • Lidong Wang
  • Peng Wu
  • Chao Gao
  • Lingqing Sun
Applied Problems
  • 3 Downloads

Abstract

Traditional wildfire detection methods are of low efficiency and cannot meet user needs, a novel method based on deep time and space features along transmission line is proposed in this paper, which uses ViBe algorithm to detect movements in videos, and extracts static deep feature in the space domain and dynamic optical flow feature in the time domain respectively. At last the deep convolutional neural network model in cascade is used to classify and find out real wildfire regions. By using combined deep features extracted from dynamic time-domain and static space-domain respectively, our method can eliminate the interference of movements of other objects with similar colors.

Keywords

wildfire detection ViBe algorithm deep convolutional neural network model 

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Copyright information

© Pleiades Publishing, Ltd. 2018

Authors and Affiliations

  • Jie Yuan
    • 1
  • Lidong Wang
    • 2
  • Peng Wu
    • 1
  • Chao Gao
    • 3
  • Lingqing Sun
    • 1
  1. 1.Jiangsu Electric Power Information Technology Co., Ltd.NanjingChina
  2. 2.Qianjiang CollegeHangzhou Normal UniversityHangzhou, ZhejiangChina
  3. 3.State Grid Jiangsu Electric Power CompanyNanjingChina

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