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Title
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تشخيص دود و آتش با تحليل موجك و مشخصات بي نظمي
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Type
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Presentation
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Keywords
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Fire and smoke detection, Wavelet analysis,
Disorder features, Color and motion features.
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Abstract
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The fire and smoke monitoring systems are useful in
different industry such as military, social security and
economical. The recent methods for fire and smoke detection
are used only motion and color characteristics thus many
wrong alarms are happening and this is decrease the
performance of the systems. This research presents a new
method for fire and smoke detection through image processing.
In this algorithm all objects in an image is considered and then
check them to figure out which objects are smoke and fire.
The color, motion and disorder are useful characteristics in
fire and smoke detection algorithm. Smoke of fire will blur the
whole or part of the images. Thus by processing of the video
frames, different objects will detect. Due to evaluate the
features of objects, the goal objects (fire and smoke) can be
defined easily. Two-dimensional wavelet analysis is used in the
presented method. The results of this research present the
proposed features that can reduce the wrong alarms and
increase the system performances.
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Researchers
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Reza Dianat (Third researcher) ,
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