基于颜色增强变换和MSER检测的烟雾检测算法

Video Smoke Detection Based on Color Transformation and MSER

在远距离烟雾视频监控中,当烟雾区域小或运动缓慢时,烟雾检测变得非常困难,为了解决这一问题,提出了一种基于烟雾增强颜色变换和MSER(maximally stable extremal regions)检测的烟雾检测算法.首先提出了一种新型烟雾增强颜色变换,可使变换后图像中烟雾区域更加突出,便于后续的分割;其次在变换图像上检测MSER区域,分割出烟雾区域,避免了基于颜色信息或运动信息等传统方法难以准确分割烟雾的缺点;最后针对烟雾的特点,提出了烟雾的静态和动态判据,并以通过静态和动态判据的次数判定是否为烟雾,并进行报警.实验结果表明,该算法可在远距离烟雾视频监控中准确地检测出烟雾区域,具有较高的可靠性.

In the long-range video surveillance, the smoke is difficult to detect when the smoke is small or it moves slowly. In order to solve this problem, a video smoke detection algorithm based on smoke color enhancement transform and maximally stable extremal regions （MSER） was proposed. Firstly, a smoke color enhancement transformation was proposed to make the smoke area more salient and easier to be segmented. Secondly, in order to avoid the difficulty of smoke segmentation in the traditional color-based and motion-based methods, the MSER detection was employed to segment the smoke area. Lastly, based on the accurate segmentation, a series of static and dynamic criterions for the characteristics of smoke was proposed and the smoke was determined by the cumulative number of passing through these static and dynamic criterions. Experimental results show that the proposed algorithm can accurately and reliability detect the smoke in the far-range video surveillance.