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.
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