Using the Thresholds Function Method to Detect License Plates

Abstract

License plate recognition is very important technology for regulating an automobile society. However, doing so it is very difficult, because a background and a car surface color can be similar to that of the license plate. Furthermore, detecting license plates when cars are moving at a very high speed is difficult. In this paper, We propose a new method of extracting car license plates automatically by using a real-coded genetic algorithm (RGA). Using the proposed RGA, the most likely plate colors can be detected under various light conditions. First, the average brightness Y value of images are calculated. Next, the retation between the Y value and the most likely plate color thresholds upper and lower bounds are obtained with the RGA to estimate threshold equations. To prove the effectiveness of the proposed method, we describe simulations performed using real images.