Improved Gaussian Mixture Model Research Articles

Multi-feature fusion based fast video flame detection

A video flame detection method based on the multi-feature fusion is presented in this paper. The temporal and spatial characteristics of flames, such as ordinary flame movement and color clues, a flame flickering detection algorithm is incorporated into the scheme to detect fires in color video sequences. An improved Gaussian mixture model method is firstly adopted to extract moving foreground objects from the still background of detection scenes; secondly, detected moving objects are then categorized into candidate and non-candidate flame regions by using a flame color filtering algorithm; finally, a flame flicker identification algorithm based on statistical frequency counting is used to distinguish true flames from fire-like objects in video images. Testing results show that the proposed algorithms are effective, robust and efficient. The processing rate of the flame detection method can achieve 24 fps with image size of 320 × 240 pixels on a PC with an AMD 2.04 GHz processor.