Wildfire smoke detection using computational intelligence techniques

In this paper, we propose an image processing system for the detection of wildfire smoke based on computational intelligence techniques and capable of adapting to different applicative environments. The proposed system is designed for processing with limited computational complexity. The detection process focuses on the extraction of specific features of wildfire smoke. A computational intelligence classifier is adopted to identify the presence of smoke. In order to test its effectiveness, the proposed system has been tested with low quality frame sequences, providing the capability to deal also with low cost cameras. The results indicate that the proposed approach is accurate and can be effectively applied in different environmental conditions.