Share Email Print
cover

Proceedings Paper • new

Early wildfire smoke detection based on improved codebook model and convolutional neural networks
Author(s): Bin Zhang; Wei Wei; Bingqian He; Chuanlei Guo
Format Member Price Non-Member Price
PDF $14.40 $18.00

Paper Abstract

For the current detection methods are not flexible and detection performance is not high, in this paper, we present a new method of video-based smoke detection algorithm by combining the improved codebook model and the Convolutional Neural Networks (CNNs). Firstly, the algorithm detects the suspected smoke regions by the improved codebook model. Secondly, it uses the deep Convolutional Neural Networks (CNNs) to extract the features of the suspected smoke area automatically, and then classify these features into smoke or non-smoke. Compared with the previous work, experimental results have shown that the detection precision in the testing sets can reach high performance. In addition, through the experiments on more than one video scene, it shows the effectiveness of our method and improves the smoke detection ability.

Paper Details

Date Published: 9 August 2018
PDF: 8 pages
Proc. SPIE 10806, Tenth International Conference on Digital Image Processing (ICDIP 2018), 108065X (9 August 2018); doi: 10.1117/12.2502974
Show Author Affiliations
Bin Zhang, Chengdu Univ. of Information and Technology (China)
Wei Wei, Chengdu Univ. of Information and Technology (China)
Bingqian He, Chengdu Univ. of Information and Technology (China)
Chuanlei Guo, Chengdu Univ. of Information and Technology (China)


Published in SPIE Proceedings Vol. 10806:
Tenth International Conference on Digital Image Processing (ICDIP 2018)
Xudong Jiang; Jenq-Neng Hwang, Editor(s)

© SPIE. Terms of Use
Back to Top