改进的遗传算法在车牌自动识别系统中的应用

在车牌自动识别系统中，如何选择对车牌字符分类能力强的特征组合是系统面临的关键问胚。针对传统组合优化方法用于特征选择的种种缺陷和简单遗传算法过早收敛的缺点，提出了利用伪并行、最优解保存和自适应参数调整相结合的改进的遗传算法对提取的车牌字符图像众多特征进行优化选择的策略。仿真实验证明，改进的遗传算法不但从收敛速度和搜索能力上优于简单的遗传算法，而且可以有效的避免出现早熟现象，防止陷入局部最优；所提出的特征选择算法不仅提高了车牌字符识别率。而且识别结果十分稳定。

Application of Revised Genetic Algorithm in the Automatic Recognition System of Vehicle License

In the automatic recognition system of vehicle license,feature selection for vehicle character recognition is the key factor in pattern recognition.In view of the deficiencies of traditional combination optimization method and the shortcoming of too early convergence of simple genetic algorithm,a new method of feature selection based on a revised genetic algorithm of pseudo-parallel combined with optimum solution reservation and adaptive parameter adjustment is proposed.The results of the simulation show that the revised genetic algorithm not only is better than the simple genetic algorithm in respect of convergence speed and search ability,but also can effectively avoid appearing precocity and plunging into local optimum.What's more the experimental results indicate that the vehicle character recognition rates are improved significantly and the classification results are very robust using the proposed method.