An intelligent and real-time system for plate recognition under complicated conditions

Vehicle Plate Recognition (VPR) algorithm in images and videos usually consists of the following three steps: 1) Region extraction of the plate (plate localization), 2) characters segmentation of the plate 3) Recognition of each character. This paper presents new methods for real-time plate recognition in each step. We used a Detector for the Blue Area (DBA) to locate the plate, Averaging of White Pixels in Objects (AWPO) for the character segmentation, then of method the Euclidian distance and template matching for character recognition after training. This system used 250 vehicle images with different backgrounds and non-uniform conditions. The proposed system is robust against challenges such as illumination and distance changes, and different angles between camera and vehicle, the presence of shadow, scratches and dirt on the plates. The accuracy rate for the three stages are 91.6% 89% and 95.09% respectively. The real-time recognition of plates for vehicles is 2.3 seconds, too.