Comparison of intensity flickering features for video based flame detection algorithms

• Comparison of the performance of several flickering features.
• Feature elements that should be considered to detect flame flickering.
• High pass filtering improves flame detection rates.
• Zero crossings achieve low classification rates for flickering detection.

Flickering is the most explicit visual characteristic of flames. Flames flicker in height, size and in brightness. Video based flame detection algorithms often analyze flickering of pixel intensities over time to detect flames. In this study we investigate five different pixel intensity flickering features based on methods presented in previous work. We compare the classification rates that features achieve on a large video database containing flames and non-flame objects. We depict differences of the features to each other and explain how these differences affect the classification rates. We point out components that should be considered for the design of flickering features.