Author/Authors :
Shi, Peng School of Electronic Engineering - Beijing University of Posts and Telecommunications, China , Hou, Bin School of Electronic Engineering - Beijing University of Posts and Telecommunications, China , Chen, Jing School of Electronic Engineering - Beijing University of Posts and Telecommunications, China , Zu, Yunxiao School of Electronic Engineering - Beijing University of Posts and Telecommunications, China
Abstract :
As more and more surveillance cameras are deployed in the Internet of Things, it takes more and more work to ensure the cameras are not occluded. An algorithm of detecting whether the surveillance camera is occluded is proposed by comparing the similarity of the images in this paper. Firstly, the background modeling method based on frame difference is improved. The combination method of the background difference and frame difference is proposed, and the experimental results showed that the combination algorithm can extract the background image of the video more quickly and accurately. Secondly, the LBP (Local Binary Patterns) algorithm is used to compare the similarity between the background image and the reference image. By changing the window size of the LBP algorithm and setting an appropriate threshold, the actual demands can be satisfied. So, the algorithms proposed in this paper have high application value and practical significance.
