Gaussian Mixture Model Based Smoke Detection Algorithm Robust to Lights Variations

Gaussian 혼합모델 기반 조명 변화에 강건한 연기검출 알고리즘

  • Received : 2012.07.15
  • Accepted : 2012.08.09
  • Published : 2012.08.31


In this paper, a smoke detection algorithm robust to brightness and color variations depending on time and weather is proposed. The proposed smoke detection algorithm specifies the candidate region using difference images of input and background images, determines smoke by comparing feature coefficients of Gaussian mixture model of difference images. Thresholds for specifying candidate region is divided by four levels according to average brightness and chrominance of input images. Clusters of Gaussian mixture models of difference images are aligned according to average brightness. Smoke is determined by comparing distance of Gaussian mixture model parameters. The proposed algorithm is implemented by media dedicated DSP. As results of experiments, it is shown that the proposed algorithm is effective to detect smoke with camera installed outdoor.


Supported by : 경성대학교


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