Research of Smoke Detection on Visual Saliency Method

Abstract

Smoke detection is the key to the early warning of the fire, and it is hard to reach the unified standard of the smoke detection because of different environments and different combustions. Considering the continuity of the occurrence of smoke and the more obvious visual saliency along with the long-time integration, the paper proposes the algorithm of multi-step accumulation of inter-frame difference in order to rapidly find out the regions in which moving targets in video can appear, which can reduce the detection range. In the small matrix in the motion region, the matrix of low rank and sparse decomposition are adopted to separate the moving foreground object from the background. In the complex outdoor scene, the smoke’s drift motility and the color’s translucence are more obvious, and the smoke target can be locked by means of the growth for all motion region and the saliency detection in HSV color space. The experiment compares the current mainstream salient algorithms which are applied to the smoke detection. The method of detecting speed and accuracy which is used in the paper has achieved a good effect. The method can be applied in different video scenes, even in the low-resolution and strong-noise scenes, it can also achieve a better detection result.