The existing background modeling algorithms are in general quite sensitive to local illumination mutation in the scene. Therefore

a new temporal and spatial center-symmetric local binary pattern (TSCS-LBP) operator is proposed

and a background modeling algorithm based on the TSCS-LBP histogram is designed. The proposed operator extracts temporal information based on the center-symmetric local binary pattern (CS-LBP) operator. Considering the lighting environment

the pixel gray value itself has an important role. So the proposed operator includes the center pixel value information. Meanwhile

this operator uses the Niblack algorithm as the threshold of the local binary pattern. The threshold has an illumination factor

which can adjust adaptively according to the lighting situations in different regions. Owing to these techniques

the proposed operator can adapt to local illumination mutation quickly

while keeping a low computational complexity. The background modeling algorithm based on the proposed TSCS-LBP operator can detect foreground objects more accurately in the common experimental scene

and has higher noise immunity and testing accuracy. Meanwhile

the proposed algorithm has a good ability to adapt to scenes having local illumination mutation and it is better than existing algorithms. The experimental results prove the effectiveness and robustness of the proposed algorithm.