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Compared with traditional methods, video smoke detection has many advantages, such as fast response, noncontact and so forth. For the sake of detecting smoke in the nighttime with 0 lux around, the paper presents a smoke recognition method based on active infrared CCD video image. Experimental results show that it can well recognize smoke to reach the aim of smoke-detection in the nighttime, by extracting...
A novel video smoke recognition method based on optical flow is presented. The result of optical flow is assumed to be an approximation of motion field. The method is proposed as following, first, moving pixels and regions in the video are determined by a background estimation method. Then, a pyramidal implementation of the Lucas Kanade feature tracker is proposed to calculate the optical flow of...
A novel video smoke detection method using both color and motion features is presented. The result of optical flow is assumed to be an approximation of motion field. Background estimation and color-based decision rule are used to determine candidate smoke regions. The Lucas Kanade optical flow algorithm is proposed to calculate the optical flow of candidate regions. And the motion features are calculated...
Since the texture is an important feature of smoke, a novel method of texture analysis is proposed for real-time fire smoke detection. The texture analysis is based on gray level co-occurrence matrices (GLCM) and can distinguish smoke features from other none fire disturbances. For the realization of real-time fire detection, block processing technique is adopted and the computation of texture features...
This paper proposes a method for smoke detection in video based on wavelet transformation. Wavelet transformation is one of the most popular methods in image processing. Using it, here we get the edge-area-information of the scenes. We make a video processing platform by VC-Programming, and design some smoke experiments. Then we use the platform to process the smoke videos and get the total energy...
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