Super-resolution Reconstruction for License Plate Image in Video Surveillance System

In order to improve the recognition of license plate texts in the real traffic surveillance video, super-resolution reconstruction (SR) method is applied to reconstruct a high-resolution (HR) image from consecutive frames in the video sequence. Current SR methods almost focus on small local translation and rotation, which limits the reconstruction of fast moving or significantly zooming objects, such as license plate images in surveillance video. In this paper, we combine Fourier-Mellin transform (FMT) and Vandewalle's algorithm into a new technique to improve the registration accuracy of license plate image. FMT is introduced for scaling estimation, while Vandewalle's algorithm is utilized for rotation and translation estimation. Additionally, the image reconstruction is carried out by the projection onto convex sets (POCS) method. The experiments on simulated and real image sequences are carried out respectively, and the results demonstrate that our approach can achieve better performance on reconstructing a HR license plate image.