  In this article, a video base early fire alarm system is developed by
monitoring the smoke in the scene. There are two major contributions in this
work. First, to find the best texture feature for smoke detection, a general
framework, named Histograms of Equivalent Patterns (HEP), is adopted to achieve
an extensive evaluation of various kinds of texture features. Second, the
\emph{Block based Inter-Frame Difference} (BIFD) and a improved version of
LBP-TOP are proposed and ensembled to describe the space-time characteristics
of the smoke. In order to reduce the false alarms, the Smoke History Image
(SHI) is utilized to register the recent classification results of candidate
smoke blocks. Experimental results using SVM show that the proposed method can
achieve better accuracy and less false alarm compared with the state-of-the-art
technologies.
