Fusion of thermal infrared and visible spectrum video for robust surveillance

This paper presents an approach of fusing the information provided by visible spectrum video with that of thermal infrared video to tackle video processing challenges such as object detection and tracking for increasing the performance and robustness of the surveillance system. An enhanced object detection strategy using gradient information along with background subtraction is implemented with efficient fusion based approach to handle typical problems in both the domains. An intelligent fusion approach using Fuzzy logic and Kalman filtering technique is proposed to track objects and obtain fused estimate according to the reliability of the sensors. Appropriate measurement parameters are identified to determine the measurement accuracy of each sensor. Experimental results are shown on some typical scenarios of detection and tracking of pedestrians.