License Plate Identification And Vehicle Queue Length Of Research

Intelligent transportation system is an effective way to solve the problems of traffic jam, environmental pollution in modern city. The intelligent transportation system combines with electronic sensor technology, image processing, data communication technology, electronic control technology, information processing technology and so on. Its purpose is to set up a directing ground traffic system, fulfilling the exact, valid system in modern society. The identification of the license plate and the measure of vehicle queue length are essential parts of intelligent transportation system. The identification of the license plate and the measure of vehicle queue length applicants many technologies, such as synthesize computer vision technology, the image processing, and the pattern recognition and so on.Fully considering characteristics of license plate and image in real life, the paper proposes an enhance K-means algorithm. The main segmentation can be completed through the use of cluster center and connection. Thus it can be prepared for the extraction of many car numbers.Comparing with the data from standard database, the data based on statistical gray values level change frequency and character occupied area are more accurate and simple to identification characters.Vehicle queue length measurement uses the improved Canny edge detection algorithm. The new algorithm improves the calculation template of the Canny algorithm. The improved Canny algorithm computes the vehicle queue length by counting energy points.This measure is very effective. All the experimental images come from the real life, including parking areas, roads, and communities. The results of the experiment show that this method can distinguish the vehicle license and the queue length. The measure is very useful and full of robustness.