In this paper, we present a new vision-based algorithm for fire detection problem. The algorithm consists of three main tasks: pixel-based processing to identify potential fire blobs, blob-based statistical feature ex...
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ISBN:
(纸本)9781479934003
In this paper, we present a new vision-based algorithm for fire detection problem. The algorithm consists of three main tasks: pixel-based processing to identify potential fire blobs, blob-based statistical feature extraction, and a support vector machine classifier. In pixel-based processing phase, five feature vectors based on RGB color space are used to classify a pixel by using a Bayes classifier to build a potential fire mask (PFM) of image. Next step, a potential fire blob mask (PFBM) is computed by using the difference between two consecutive PFM and a recover technique. In blob-based phase, for each potential blob in a potential fire blobs image (PFBI) an 7-feature vector are evaluated;this vector includes three statistical features of colour, four texture parameters and one shape roundness parameter. Finally, a SVM classifier is designed and trained for distinguish a potential fire blob are fire or fire-like object. Experimental results demonstrate the effectiveness and robustness of the proposed method.
based on the three-dimensional (3-D) noise model, main noise sources of single detector scanning, serial scanning, parallel scanning parallel output and staring systems are analyzed respectively. And it is assumed tha...
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ISBN:
(纸本)0819442763
based on the three-dimensional (3-D) noise model, main noise sources of single detector scanning, serial scanning, parallel scanning parallel output and staring systems are analyzed respectively. And it is assumed that all noise is Gaussian distributed. Then models are established. In addition, non-linearity is discussed and simulated. With the method of pixel-based processing, these models are implemented. Finally, the results are shown and discussed.
We introduce a simple method for motion enhancement. The method enables us to realize brightness enhancement of moving objects, to reduce the influence of non-uniform illumination in motion analysis and to visualize d...
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We introduce a simple method for motion enhancement. The method enables us to realize brightness enhancement of moving objects, to reduce the influence of non-uniform illumination in motion analysis and to visualize dynamic streamlines in fluid flow analysis. (C) 1999 Elsevier Science B.V. All rights reserved.
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