A new image-based real-time flame detection method using color analysis

A new image-based real-time flame detection method is proposed in this paper. First, fire flame features based on the HSI color model are extracted by analyzing 70 flame images. Then, based on these flame features, regions with fire-like colors are roughly separated from an image. Besides segmenting fire flame regions, background objects with similar fire colors or caused by color shift resulted from the reflection of fire flames are also separated from the image. In order to get rid of these spurious fire-like regions, the image difference method and the invented color masking technique are applied. Finally, a simple method is devised to estimate the burning degree of fire flames so that users could be informed with a proper warning alarm. The proposed method is tested with seven diverse fire flame video clips on a Pentium II 350 processor with 128 MB RAM at the process speed of thirty frames per second. The experimental results are quite encouraging. The proposed method can achieve more than 96.97% detection rate on average. In addition, the system can correctly recognize fire flames within one second on the initial combustion from the test video clips, which seems very promising.