1. Video Image Fire Recognition Based on Color Space and Moving Object Detection
- Author
-
Liu Xiao-jun, Zhang Qian, and Huang Lei
- Subjects
0209 industrial biotechnology ,Fire detection ,Computer science ,business.industry ,Frame (networking) ,ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION ,ComputerApplications_COMPUTERSINOTHERSYSTEMS ,02 engineering and technology ,Color space ,Object detection ,Color model ,020901 industrial engineering & automation ,0202 electrical engineering, electronic engineering, information engineering ,Graph (abstract data type) ,RGB color model ,020201 artificial intelligence & image processing ,Computer vision ,Noise (video) ,Artificial intelligence ,business ,ComputingMethodologies_COMPUTERGRAPHICS - Abstract
Flame recognition based on video image is an important method for fire detection. In order to improve the accuracy of flame recognition and the applicability of complex scenes, the flame color model was improved on the basis of RGB and HSI color space models, and the flame color model with adaptive threshold values was proposed for different background spaces, which could be adapted to the extraction of suspected flame areas in different environments. The flame has motion characteristics during combustion. ViBe(Visual Background Extractor) algorithm can quickly identify moving objects, but it cannot detect moving objects quickly when the first frame of the image contains moving objects. In this paper, an improved ViBe algorithm is proposed. Frame difference method is used to build the background model through the difference of the first two frames. The method of combining three frame difference and VIBE algorithm can reduce the influence of noise. The hole in the target graph is solved through image morphology processing. Experiments show that the algorithm can identify the flame region accurately and quickly.
- Published
- 2020