公开(公告)号：US20190095730A1

公开(公告)日：2019-03-28

申请号：US16136128

申请日：2018-09-19

Applicant: Beijing University of Posts and Telecommunications

Inventor： Huiyuan FU ,  Huadong MA ,  Yifan ZHANG ,  Yu CAO ,  Dengkui ZHANG

IPC: G06K9/00 ,  G06K9/46 ,  G06T3/40 ,  G06N3/08

Abstract: Embodiments of the present invention provide an end-to-end lightweight method and apparatus for license plate recognition. The method comprises: obtaining an image to be recognized; obtaining a number of a license plate in the image to be recognized and position coordinates of the license plate in the image to be recognized on the basis of the image to be recognized and a pre-trained target license plate recognition model, wherein the target license plate recognition model comprises a target feature extraction network, a target region candidate localization network, a target super-resolution generation network and a target recurrent neural network. Because in this solution, once an image to be recognized is input into the target license plate recognition model, the target license plate recognition model can output the license plate number and position coordinates of the license plate in the image to be recognized, one realizes an end-to-end model. The model has relatively strong robustness, and it can detect and recognize pictures taken under different camera angles. Moreover, computation variables such as image features can be reused without repeated computations, the model takes up less RAM and the speed of license plate recognition is greatly improved.