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.

The Automatic License Plate Recognition (ALPR) system has wide application and very important in the Intelligent Transportation System (ITS) such as the Electronic Toll Collection (ETC) system. The purpose of this paper is designing an Automatic License Plate Recognition (ALPR) system, which will be applied for one-stop and non-stop ETC in Vietnam. Our ALPR system consists of two major parts: the first part is hardware system and the second part is software system. In the first part, the price, types of equipments and technology will be considered for designing, which satisfied for Vietnam environment, Vietnam regulation in the road pricing rules and Vietnam standard of ETC. In the second part, we will combined image processing technology and artificial neural network to proposed a improved software system, our software include four modules: image capture, license plate location, characters segmentation and characters recognition. Our ALPR software will be tested by 700 Vietnam vehicle images, which obtained from actual system and complex background: lightening conditions (night & day), license angles, illumination, size and type, colors and reflected light. Our ALPR software is more effective than some of the existing methods earlier, the efficiency of computing time & accuracy is improved and very satisfied for all types of Vietnam LP and Vietnam environment.

In the Automatic License Plate Recognition (ALPR) system, the License Plate Location (LPL) is the key step before the final recognition. This paper proposed an improved LPL algorithm for Vietnam vehicle license plates (LP). The proposed algorithm consists of three main modules: Pre-processing (convert RGB image to grayscale image, adjust grayscale image intensity, image binarization use Otsu method), LP candidates location (morphology opening to remove noises & dilation operation, measure properties of image regions to find candidates), LP exactly location (finding the LP angle & rotating LP, cut exactly LP region). We implemented test for 350 Vietnam vehicle images, which obtained from the actual system, the average rate of accuracy of our method is 98.64%, our results are more exactly presented methods.