Real-time smoke detection for surveillance

This paper introduces the smoke detection method for surveillance cameras. The background subtraction was used to determine moving objects. Color probability was utilized to find possible smoke pixels in a scene. Separate pixels, acquired by background subtraction, were united by morphological operations and connected components labeling methods. The existence of the smoke region is then confirmed by boundary roughness and edge density. In the last step, the current frame is compared to the previous one in order to check the behavior of objects. The most computationally expensive steps are processed in parallel using CUDA to achieve real-time performance. Computational time was decreased by more than 6 times comparing to the CPU processing only.