Adaptive Targets-deteeting Algorithm based on LBP and Background Modeling under Complex Scenes

摘要

Improving the robustness of targets-detecting algorithm under complicated scenes is an important and difficult research problem in the field of computer vision. In order to achieve accurate and robust detecting result under complex scenes, with all kinds of background disturbance and shadow, an adaptive targets-detecting algorithm based on LBP and background modeling method (BMM) is proposed in this paper. Firstly, BMM combined with LBP, which is less influenced by shadow than traditional Color-based BMM, is presented. Secondly, light information pretreatment is proposed for situation of sudden brightness changes. Finally, an adaptive detecting mechanism is proposed. Experimental results show that, the proposed algorithm has robustness for most background disturbances, effectively improved adaptability, real-time performance and accuracy of detecting effect under complex scenes.