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2010 | OriginalPaper | Chapter

Transmission: A New Feature for Computer Vision Based Smoke Detection

Authors : Chengjiang Long, Jianhui Zhao, Shizhong Han, Lu Xiong, Zhiyong Yuan, Jing Huang, Weiwei Gao

Published in: Artificial Intelligence and Computational Intelligence

Publisher: Springer Berlin Heidelberg

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A novel and effective approach is proposed in this paper to detect smoke using transmission from image or video frame. Inspired by the airlight-albedo ambiguity model, we introduce the concept of transmission as a new essential feature of smoke, which is employed to detect the smoke and also determine its corresponding thickness distribution. First, we define an optical model for smoke based on the airlight-albedo ambiguity model. Second, we estimate the preliminary smoke transmission using dark channel prior and then refine the result through soft matting algorithm. Finally, we use transmission to detect smoke region by thresholding and obtain detailed information about the distribution of smoke thickness through mapping transmissions of the smoke region into a gray image. Our method has been tested on real images with smoke. Compared with the existing methods, experimental results have proved the better efficiency of transmission in smoke detection.

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Metadata
Title
Transmission: A New Feature for Computer Vision Based Smoke Detection
Authors
Chengjiang Long
Jianhui Zhao
Shizhong Han
Lu Xiong
Zhiyong Yuan
Jing Huang
Weiwei Gao
Copyright Year
2010
Publisher
Springer Berlin Heidelberg
DOI
https://doi.org/10.1007/978-3-642-16530-6_46

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