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Proceedings Paper

Cigarette smoke detection from captured image sequences
Author(s): Kentaro Iwamoto; Hironori Inoue; Toru Matsubara; Toshihisa Tanaka
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Paper Abstract

We investigate a detection of smoke from captured image sequences. We propose to address the following two problems in order to attain this goal. The first problem is to estimate candidate areas of smoke. The second problem is to judge if smoke exists in the scene. To solve the first problem, we apply the previously proposed framework where image sequences are divided into some small blocks and the smoke detection is done in each small block. In this framework, we propose to use color and edge information of the scene. To solve the second problem, we propose a method for judging if smoke exists in the scene by using the areas of smoke obtained in the last step part. We propose some feature values for judging if smoke exists in the scene. Then, by simulation we find the best combination of feature values. In addition, we study the effect of normalization, which provide better performance in recognition.

Paper Details

Date Published: 29 January 2010
PDF: 10 pages
Proc. SPIE 7538, Image Processing: Machine Vision Applications III, 753813 (29 January 2010); doi: 10.1117/12.840133
Show Author Affiliations
Kentaro Iwamoto, Tokyo Univ. of Agriculture and Technology (Japan)
Hironori Inoue, Tokyo Univ. of Agriculture and Technology (Japan)
Toru Matsubara, Tokyo Univ. of Agriculture and Technology (Japan)
Toshihisa Tanaka, Tokyo Univ. of Agriculture and Technology (Japan)


Published in SPIE Proceedings Vol. 7538:
Image Processing: Machine Vision Applications III
David Fofi; Kurt S. Niel, Editor(s)

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