Abstract: It is of great military value and practical significance to establish a quantitative law of laser interference to infrared imaging system. The influence of 10.6 μm pulse laser on the target extraction and tracking performance of infrared imaging detectors was deeply analyzed by using the Canny edge extraction algorithm based on contour curvature and cross-correlation template matching algorithm. The normalized correlation between target images and interference images under different target positions and power conditions was used to quantitatively describe the laser interference effect, and an evaluation system with evaluation factors of target distance and laser power was determined to assess the interference level and whether recognition was possible. The results show that the Canny edge extraction algorithm based on contour curvature divides pixels into strong information points, weak information points, and no information points based on curvature, making the algorithm adaptively at the pixel level, and better preserves the detail information of the image. According to the experiments, laser power and target position are the key factors affecting the detection performance of laser interference on infrared imaging guided weapon targets. The evaluation system can balance the importance of target position distance and laser power in the evaluation of laser interference images, and it is found that laser interference will produce many false edge information, which will seriously affect the performance of pattern recognition algorithms. Finally, the evaluation formula is consistent with the experimental results, which can objectively reflect the degree of influence of laser interference on the target extraction and tracking performance of infrared imaging systems.