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Real-time detection of steam in video images

9 years 9 months ago
Real-time detection of steam in video images
In this paper, we present a real-time image processing technique for the detection of steam in video images. The assumption made is that the presence of steam acts as a blurring process, which changes the local texture pattern of an image while reducing the amount of details. The problem of detecting steam is treated as a supervised pattern recognition problem. A statistical hidden Markov tree (HMT) model derived from the coefficients of the dual-tree complex wavelet transform (DT-CWT) in small 48 × 48 local regions of the image frames is used to characterize the steam texture pattern. The parameters of the HMT model are used as an input feature vector to a support vector machine (SVM) technique, specially tailored for this purpose. By detecting and determining the total area covered by steam in a video frame, a computerized image processing system can automatically decide if the frame can be used for further analysis. The proposed method was quantitatively evaluated by using a labe...
Ricardo J. Ferrari, H. Zhang, C. R. Kube
Added 27 Dec 2010
Updated 27 Dec 2010
Type Journal
Year 2007
Where PR
Authors Ricardo J. Ferrari, H. Zhang, C. R. Kube
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