Smoke Detection Based on Image Analysis Technology

  • Huiqing Zhang
  • Jiaxu ChenEmail author
  • Shuo Li
  • Ke Gu
  • Li Wu
Conference paper
Part of the Communications in Computer and Information Science book series (CCIS, volume 1181)


Ecological problems and pollution problems must be faced and solved in the sustainable development of a country. With the continuous development of image analysis technology, it is a good choice to use machine to automatically judge the external environment. In order to solve the problem of smoke extraction and exhaust monitoring, we need the applicable database. Considering the number of databases that can be used to detect smoke is small and these databases have fewer types of pictures, we subdivide the smoke detection database and get a new database for smoke and smoke color detection. The main purpose is to preliminarily identify pollutants in smoke and further develop smoke image detection technology. We discuss eight kinds of convolutional neural network, they can be used to classify smoke images. Testing different convolutional neural networks on this database, the accuracy of several existing networks is analyzed and compared, and the reliability of the database is also verified. Finally, the possible development direction of smoke detection is summarized.


Smoke detection Image analysis technology Image database 


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Copyright information

© Springer Nature Singapore Pte Ltd. 2020

Authors and Affiliations

  • Huiqing Zhang
    • 1
    • 2
  • Jiaxu Chen
    • 1
    • 2
    Email author
  • Shuo Li
    • 1
    • 2
  • Ke Gu
    • 1
  • Li Wu
    • 1
  1. 1.Faculty of Information TechnologyBeijing University of TechnologyBeijingChina
  2. 2.Engineering Research Center of Digital Community, Ministry of EducationBeijingChina

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