License plate recognition is very important in an automobile society. However, it is very difficult to do it, because a background and a body color of cars are similar to that of the license plate. Furthermore, the detection of cars in a moving at a very high-speed is difficult to be done. In this paper, we propose a new robust thresholds determination method in the various background by using the real coded genetic algorithm (RGA). By using RGA, the most likely plate colors are decided under various light conditions. First, the average brightness Y values of images are calculated. Next, relationship between the Y value and the most likely plate color thresholds (upper and lower bounds) are obtained by GA to estimate threshold equations by using the recursive least squares (RLS) algorithm. Finally, in order to show the effectiveness of the proposed method, we show simulation examples by using real images, and result rate of detection is 85.0%.
|出版ステータス||Published - 2003 9 24|
|イベント||International Joint Conference on Neural Networks 2003 - Portland, OR, United States|
継続期間: 2003 7 20 → 2003 7 24
|Other||International Joint Conference on Neural Networks 2003|
|Period||03/7/20 → 03/7/24|
ASJC Scopus subject areas
- Artificial Intelligence