15 November 2017 Dissipation function and adaptive gradient reconstruction based smoke detection in video
Author Affiliations +
Proceedings Volume 10605, LIDAR Imaging Detection and Target Recognition 2017; 1060534 (2017) https://doi.org/10.1117/12.2295197
Event: LIDAR Imaging Detection and Target Recognition 2017, 2017, Changchun, China
Abstract
A method for smoke detection in video is proposed. The camera monitoring the scene is assumed to be stationary. With the atmospheric scattering model, dissipation function is reflected transmissivity between the background objects in the scene and the camera. Dark channel prior and fast bilateral filter are used for estimating dissipation function which is only the function of the depth of field. Based on dissipation function, visual background extractor (ViBe) can be used for detecting smoke as a result of smoke’s motion characteristics as well as detecting other moving targets. Since smoke has semi-transparent parts, the things which are covered by these parts can be recovered by poisson equation adaptively. The similarity between the recovered parts and the original background parts in the same position is calculated by Normalized Cross Correlation (NCC) and the original background’s value is selected from the frame which is nearest to the current frame. The parts with high similarity are considered as smoke parts.
© (2017) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Bin Li, Bin Li, Qiang Zhang, Qiang Zhang, Chunlei Shi, Chunlei Shi, } "Dissipation function and adaptive gradient reconstruction based smoke detection in video", Proc. SPIE 10605, LIDAR Imaging Detection and Target Recognition 2017, 1060534 (15 November 2017); doi: 10.1117/12.2295197; https://doi.org/10.1117/12.2295197
PROCEEDINGS
7 PAGES


SHARE
Back to Top