Distance Estimation for Precise Object Recognition Considering Geometric Distortion of Wide-angle Lens

Face and license plate recognition are crucial aspects in the field of intelligent security. A high-spatial-resolution imaging system with a large-format detector and low-distortion optical lens is required for recognizing small-scale features and rich details in faces and license plates. However, security systems need to monitor wide area, which requires a wide-angle lens with a wide field of view, but with some distortion. Therefore, precise target recognition should be used as a constraint to balance the high spatial resolution and wide field of view when designing an imaging system that can recognize details and monitor a wide area. Under such application requirements, an evaluation index based on pixel areal density is proposed. With the aid of this evaluation index, a distance estimation method for precise object recognition, considering the radial distortion of the wide-angle lens, was designed. Rotated and translated faces and license plates were used to demonstrate the estimation method. The results indicate that the recognition distance with radial distortion is less than that without radial distortion. When the translation distance is 1 m and 2 m, the difference between the actual recognition distance and the ideal recognition distance is 34.2% and 27.5%, respectively.