An Improved Method for Vietnam License Plate Location, Segmentation and Recognition

The Automatic License Plate Recognition (ALPR) is very important in the Intelligent Transportation System (ITS). In this paper we proposed an improved ALPR algorithm for Vietnam license plates (LP), which consists of three main modules: license plate location (LPL), character segmentation, character recognition. In the location work, we have improved algorithm based on edge detection, image subtraction, mathematic morphology to locate LP region, which considered removing noise. In the segmentation work, we have improved algorithm to get the segments in the LP by the peak-to-valley method in order to segment in digit images getting the two bounds of the each digit according to the statistical parameter. In the recognition work, we have used a Multi Layer Perceptron (MLP) neural network and back-propagation (BP) algorithm to recognize characters & numbers of the Vietnam LP, we used two networks for characters & numbers training with noises, in which the computing time and accuracy is improved. Our approach is more effective than some of the existing methods earlier and satisfied for Vietnam LP. We have been implemented on 600 images taken from actual scenes, different background such as light conditions (night and day), angles, illumination, size and type, colors, reflected light, dynamic conditions. The efficiency of the proposed approach is improved and average rate of accuracy of the one-row LP is 96.93%, two-row LP is 95.82%, higher than most of previous works.